225 Integer Jobs - Page 6

Company Profile : That's My Craft interior designing studio operating since 2016. We specialised in providing comprehensive turnkey solutions for a wide range of integer design projects. With a close-knit team we strictly work with fresh philosophy every time. Responsibilities : The key responsibilities area (KRA) of 2D Interior Designer :- 1. Drawing & Drafting - Develop 2D floor plans, furniture space planning , Furniture elevations, sections, and detailed working drawings (Civil work, electrical, plumbing, Reflected celling plan (RCP), etc.) - Convert site measurements, concept sketches, and verbal inputs into clear technical drawings - Prepare detailed drawings for custom furniture, cabinetry, and interior elements - Maintain a drawing library and template consistency across projects 2. Collaboration Coordinate with the design and execution team to ensure drawing accuracy and feasibility 3. Technical Accuracy Ensure that all drawings follow industry drafting standards, including proper dimensioning, layering, and annotations 4. Software & File Management - Work daily in AutoCAD, and optionally SketchUp/Layout for presentation-style 2D exports Required Skills & Qualifications - Proficiency in AutoCAD (mandatory) - Knowledge of basic SketchUp is a plus - Good understanding of interior materials, detailing, and joinery principles - Ability to interpret conceptual inputs into executable technical outputs - Familiarity with building codes, electrical, plumbing, and civil coordination basics is preferred Soft Skills - Strong attention to detail and accuracy - Ability to work under pressure and meet deadlines - Proactive communicator – ability to clarify inputs and flag drawing conflicts early - A team player with a collaborative mindset Preferred Background - Diploma/Degree in Interior Design, Architecture, or related field - 1 years of experience in 2D drafting roles within architecture or interior studios - Portfolio demonstrating technical drawing capabilities and design sensibility How to Apply: Send your resume & portfolio( showcasing relevant 3D visualization work, including examples of interior renderings and video walkthroughs) at hr@thatsmycraft.com or contact on this number +91 9023333832. Job Types: Full-time, Permanent, Fresher Pay: ₹10,000.00 - ₹15,000.00 per month Benefits: Internet reimbursement Leave encashment Paid time off Ability to commute/relocate: Gandhinagar, Gujarat: Reliably commute or planning to relocate before starting work (Required) Education: Diploma (Required) Experience: Interior design: 1 year (Required) Language: Hindi , Gujarati , English (Required) Work Location: In person

Company Profile : That's My Craft interior designing studio operating since 2016. We specialised in providing comprehensive turnkey solutions for a wide range of integer design projects. With a close-knit team we strictly work with fresh philosophy every time. Responsibilities : The key responsibilities area (KRA) of interior designer :- 1. 3D Modelling & visualisation : Assisting in creating 3D models and visualisation to help team better understand design concept. 2. Cad Drawing : Creating detailed CAD drawing and Technical documentation for design plans 3. Space Planning : Assisting on space layout, furniture arrangements and ensuring optimal space utilisation. 4. Project Documentation : Maintaining project files, documentation and ensuring designs specifications are accurately recorded. 5. Contribution to design discussions : Problem solving and understanding how to balance aesthetics and functionality. 6. Learning and Growth : Gains skills related to software, designing process, execution process with the help of senior designer and mentor. 7. Collaboration and Teamwork : Actively participating in team meeting sessions and contributing to the overall success of the design project. 8. Time Management : Complete assigned task and projects within define timeline provided by Senior designer. How to Apply: Send your resume & portfolio( showcasing relevant 3D visualization work, including examples of interior renderings and video walkthroughs) at hr@thatsmycraft.com or contact on this number +91 9023333832. Job Types: Full-time, Permanent, Fresher Pay: ₹25,000.00 - ₹45,000.00 per month Benefits: Internet reimbursement Leave encashment Paid time off Ability to commute/relocate: Gandhinagar, Gujarat: Reliably commute or planning to relocate before starting work (Required) Education: Diploma (Required) Experience: Interior design: 1 year (Required) Language: Hindi, Gujarati , English (Required) Work Location: In person

University: Delft University of Technology Country: Netherlands Deadline: 2025-08-31 Fields: Computer Science, Operations Research, Artificial Intelligence, Applied Mathematics, Statistics Are you passionate about harnessing the power of artificial intelligence to transform decision-making under uncertainty? Do you aspire to develop innovative algorithms that can offer robust and reliable recommendations for critical real-world problems? If your academic ambitions lie at the intersection of symbolic AI, optimisation, and statistical reasoning, this PhD position at TU Delft could be your gateway to cutting-edge research and impactful career opportunities. Strong and confident decision-making is at the core of many societal and engineering challenges today. Yet, the complexity and uncertainty inherent in real-world systems often make it difficult to ascertain which variables truly influence outcomes. This PhD project invites you to leverage advanced combinatorial and algorithmic methods to identify these critical parameters, thus enabling more robust, data-efficient, and reliable decision-making processes. About The University Or Research Institute Delft University of Technology (TU Delft) is one of Europe’s premier technical universities, renowned for its pioneering research, high-impact innovation, and vibrant academic community. Located in the historic city of Delft, the university boasts a strong tradition in engineering, science, and design, with a global reputation for excellence. TU Delft has been at the forefront of groundbreaking advancements, from the world-famous Dutch waterworks to state-of-the-art biotech and digital technologies. As a PhD candidate at TU Delft, you will join a diverse and international research environment, collaborating with leading experts and contributing to solutions for some of society’s most pressing challenges. Research Topic and Significance The focus of this PhD position is on Symbolic AI and Reasoning Under Uncertainty, with a particular emphasis on sensitivity analysis for decision-making models. In contemporary applications, algorithms generate recommendations based on complex models with numerous input parameters. However, determining which of these inputs genuinely drive the outcomes is crucial for resource allocation, contingency planning, and ensuring the robustness of decisions. Also See Postdoctoral Opportunity in Harmonic Mitigation for Power Electronics-Based Power Systems at… Postdoctoral Opportunity in Applied Planning and Scheduling Under Uncertainty for Offshore… Postdoctoral Opportunity in Harmonic Mitigation for Power Electronics-Based Power Systems at… PhD Position in ML-Accelerated Simulations and Uncertainty Quantification of Sustainable… PhD Opportunities in Agentic/LLM Reasoning at IDIAP/EPFL Traditional sensitivity analysis often relies on computationally intensive simulations, which may overlook significant variables. This project proposes a paradigm shift: employing logic-based and structural methods to formally identify critical parameters. By exploiting the structure of logic problems, the research aims to deliver formal guarantees on robustness, reduce computational costs, and improve the reliability of decision-support systems. This approach holds immense promise for fields such as engineering, policy-making, and societal infrastructure, where robust and explainable AI is essential. Project Details As a PhD candidate, you will be part of the Algorithmics section within the Software Technology (ST) department at TU Delft, collaborating closely with the Statistics section of the Delft Institute of Applied Mathematics (DIAM). The project is supervised by a distinguished team: dr. ir. Sicco Verwer (promotor), dr. Fabian Mies, and dr. Anna Latour (co-promotores). Your research will build upon and expand knowledge in modelling and solving paradigms such as Boolean Satisfiability, Constraint Programming, and Mixed-Integer (Linear) Programming. You will also develop methods for reasoning about discrete probability distributions, sampling complex spaces, and statistical analysis. The role involves collaboration with other researchers and software engineers to create practical tools for both academic and societal stakeholders. You will disseminate your findings through publications and presentations at leading conferences and journals, providing excellent opportunities for international networking and professional growth. The Algorithmics section is a dynamic, diverse environment where PhD and postdoc researchers work together on theoretical and algorithmic contributions to intelligent decision-making. The group addresses challenges including scalability, model learning for planning and verification, and the integration of stakeholder preferences into algorithmic processes. TU Delft’s interdisciplinary ecosystem further enhances your research experience, with opportunities to engage in cross-faculty initiatives addressing topics such as climate change, energy transition, and artificial intelligence. Candidate Profile Applicants Should Possess The Following Qualifications And Attributes – A Master’s degree in Computer Science, Operations Research, or a related field (required by the Graduate School of TU Delft). – Proficiency in the English language (see https://www.tudelft.nl/onderwijs/opleidingen/phd/admission). – Demonstrable knowledge of reasoning paradigms such as Boolean Satisfiability, Constraint Programming, or Mixed Integer (Linear) Programming (preferred). – Programming skills in languages such as Java, Python, or C++ (preferred). – Solid understanding of statistics and probability theory, particularly hypothesis testing. – Excellent critical and analytical thinking skills. – A proven record of, and interest in, further developing research skills, including self-organisation, academic writing, and a critical attitude. – Strong enthusiasm for state-of-the-art algorithmic and optimisation techniques, especially their application to decision-making. – Affinity for teaching and mentoring students. – Ability to work effectively in a team and take initiative. This position is ideal for candidates who are passionate about symbolic AI, optimisation, statistical reasoning, and who are eager to contribute to the advancement of robust decision-making methodologies. Application Process Are You Interested In This Vacancy? Please Apply No Later Than 31 Aug 2025 Via The Application Button And Upload The Following Documents – CV – Motivational letter You can address your application to Dr. Anna Latour. In addition to the required documents (your tabular CV and cover letter), we ask you to do the following: – Submit a recent example of your own academic writing (e.g., a draft of your MSc thesis). – Select 1-3 publications by Dr. Anna Latour. For each publication, please write a short paragraph addressing: (1) What you found most interesting or surprising about the research and why, and (2) What follow-up research you would propose based on your reading and why. Please submit these paragraphs along with your application. Apply via the application button and upload your tabular CV, cover letter, sample of recent academic writing, and paragraph(s) about Dr. Latour’s publication(s). Apply: https://careers.tudelft.nl/job/Delft-PhD-Position-Symbolic-AI-and-Reasoning-Under-Uncertainty-2628-CD/824585702/ Conclusion This PhD position at TU Delft offers a unique opportunity to engage in pioneering research at the intersection of symbolic AI, optimisation, and statistical reasoning. If you are driven to make a meaningful impact on decision-making methodologies and thrive in a collaborative, interdisciplinary environment, we encourage you to apply. Stay tuned to similar opportunities by following updates below this post. Want to calculate your PhD admission chances? Try it here: https://phdfinder.com/phd_admission_chance_calculator/ Get the latest openings in your field and preferred country—straight to your email inbox. Sign up now for 14 days free: https://phdfinder.com/position-alert-service/ We’re an independent team helping students find opportunities. Found this opportunity helpful? Support us with a coffee!

We're Celonis, the global leader in Process Mining technology and one of the world's fastest-growing SaaS firms. We believe there is a massive opportunity to unlock productivity by placing data and intelligence at the core of business processes - and for that, we need you to join us. The Team: The Celonis Supply Chain team is a young team of product enthusiasts that focuses on developing best-in class Business Apps in the domain of Supply Chain. Business Apps are purpose-built solutions created for a specific line of business, addressing most impactful pain points in their respective domain. The apps are best practice examples of how Celonis is used in new, innovative ways that push the boundaries of our platform. The team has a great balance of technical skills to build solutions paired with a customer focus and product management mindset to create meaningful products widely adopted across our customer base. The Role: You will gain experience in the Supply Chain and related processes and act as the interface between customers, our Go-To-Market and our Product & Engineering teams, shaping the future of Celonis’ Business Apps in this domain. Take this chance to rethink the way companies run their Supply Chain processes and help our customers to accelerate their value realization with Celonis. The work you’ll do: Work closely with customers to understand their pain points in Supply Chain with a focus on Order Management Be involved in all steps within the product development lifecycle from ideation to product development to scaling solutions across all Celonis customers Use the Celonis Process Intelligence Platform hands-on to develop new, innovative solutions in the area of Order Management Collaborate with platform product managers and engineers to guide and influence feature development of the platform Work together with our UX team to define the user experience for our products If you are passionate about Supply Chain and Order Management, the Celonis technology, and what it can do for our customers, here's your chance to directly contribute to taking our Celonis Process Intelligence Platform to the next level. The qualifications you need: 6-9+ years of experience in Solution Engineering, Implementation Consulting, Business Analytics, Operations Research or comparable roles Expert in data analysis including with tools native to the Celonis platform: SQL, PQL and Python Experience with SAP, Oracle or other ERP systems and their respective Order Management modules Operations research experience including (Mixed Integer) Linear Programming and inventory optimization is a plus Experience working with MRP is a plus Project management experience and excellent planning and organizational skills Creativity in problem solving, solution-oriented, self-motivated, able to work independently and collaborate well within and outside the team Excellent verbal and written communication skills and the willingness to work very closely with customers and cross-functional stakeholders Very good knowledge of spoken and written English. What Celonis Can Offer You: Pioneer Innovation: Work with the leading, award-winning process mining technology, shaping the future of business. Accelerate Your Growth: Benefit from clear career paths, internal mobility, a dedicated learning program, and mentorship opportunities. Receive Exceptional Benefits: Including generous PTO, hybrid working options, company equity (RSUs), comprehensive benefits, extensive parental leave, dedicated volunteer days, and much more. Interns and working students explore your benefits here. Prioritize Your Well-being: Access to resources such as gym subsidies, counseling, and well-being programs. Connect and Belong: Find community and support through dedicated inclusion and belonging programs. Make Meaningful Impact: Be part of a company driven by strong values that guide everything we do: Live for Customer Value, The Best Team Wins, We Own It, and Earth Is Our Future. Collaborate Globally: Join a dynamic, international team of talented individuals. Empowered Environment: Contribute your ideas in an open culture with autonomous teams. About Us: Celonis makes processes work for people, companies and the planet. The Celonis Process Intelligence Platform uses industry-leading process mining and AI technology and augments it with business context to give customers a living digital twin of their business operation. It’s system-agnostic and without bias, and provides everyone with a common language for understanding and improving businesses. Celonis enables its customers to continuously realize significant value across the top, bottom, and green line. Celonis is headquartered in Munich, Germany, and New York City, USA, with more than 20 offices worldwide. Get familiar with the Celonis Process Intelligence Platform by watching this video. Celonis Inclusion Statement: At Celonis, we believe our people make us who we are and that “The Best Team Wins”. We know that the best teams are made up of people who bring different perspectives to the table. And when everyone feels included, able to speak up and knows their voice is heard - that's when creativity and innovation happen. Your Privacy: Any information you submit to Celonis as part of your application will be processed in accordance with Celonis’ Accessibility and Candidate Notices By submitting this application, you confirm that you agree to the storing and processing of your personal data by Celonis as described in our Privacy Notice for the Application and Hiring Process. Please be aware of common job offer scams, impersonators and frauds. Learn more here.

The role entails advanced software development for Power Systems Applications, with a focus on delivering specific functionalities to meet corporate project and product objectives. Responsibilities include collaborating with team working with Electric Utilities or Independent System Operators (ISOs) and Transmission and Distribution System Operators to develop functional software specifications, followed by designing, coding, testing, integration, application tuning, and delivery Job Description Roles and Responsibilities As a senior member of the Software Center of Excellence, exemplifying high-quality development, testing, and delivery practices Responsible for enhancing, evolving, and supporting high-availability Electricity Energy Market Management System (MMS) Responsible for development, testing, integration, and tuning of advanced Power Systems Application software to fulfill project and product commitments Develop and evolve software in a dynamic and agile environment using the latest technologies and infrastructure Provide domain knowledge and/or technical leadership to a team of electricity markets application software engineers Support in providing budget estimates for new project tasks to project leads and managers Collaborate with customers throughout the project lifecycle to ensure software quality and functionality meet standards and requirements Interact with Product Development Teams, Customers, Solution Providers, and cross-functional teams as needed Apply SDLC principles and methodologies like Lean/Agile/XP, CI, software and product security, scalability, and testing techniques Provide maintenance of power systems application functionality, including code fixes, creating tools for model conversion, documentation, and user interfaces Support marketing efforts for proposals and demonstrations to potential customers Basic Qualification Master's degree in Electrical Power Systems with thesis or related work in power systems 5 to 8 years of experience in development or project delivery, preferably in Power Systems Analysis, Security Constrained Unit Commitment and Economic Dispatch using Mixed Integer Programming (MIP)/Optimization, or Applied Mathematics and Operations Research Desired Characteristics Continuous improvement mindset; drives change initiatives and process improvements Highly organized and efficient; adept at prioritizing and executing tasks Experience in the power systems domain Proficiency in testing and test automation Strong knowledge of source control management, particularly GitHub Demonstrated ability to learn new development practices, languages, and tools Self-motivated; able to synthesize information from diverse sources Continuously measures the completion rate of personal deliverables and compares them to the scheduled commitments Transparent in problem-solving approaches and options; determines fair outcomes with shared trade-offs Capable of defining requirements and collaborating on solutions using technical expertise and a network of experts Effective communication style for engaging with customers and cross-functional teams; utilizes product knowledge to mitigate risks and drive outcomes Strong verbal, written, and interpersonal communication skills; able to produce professional and technical reports and conduct presentations Innovates and integrates new processes or technologies to add significant value; advises on change cost versus benefits and learns new solutions to address complex problems

The role entails advanced software development for Power Systems Applications, with a focus on delivering specific functionalities to meet corporate project and product objectives. Responsibilities include collaborating with team working with Electric Utilities or Independent System Operators (ISOs) and Transmission and Distribution System Operators to develop functional software specifications, followed by designing, coding, testing, integration, application tuning, and delivery. Job Description Roles and Responsibilities As a senior member of the Software Center of Excellence, exemplifying high-quality design, development, testing, and delivery practices Responsible for enhancing, evolving, and supporting high-availability Electricity Energy Market Management System (MMS) Lead the design, development, testing, integration, and tuning of advanced Power Systems Application software to fulfill project and product commitments Develop and evolve software in a dynamic and agile environment using the latest technologies and infrastructure Provide domain knowledge and/or technical leadership to a team of electricity markets application software engineers Provide budget estimates for new project tasks to project leads and managers Collaborate with customers throughout the project lifecycle to ensure software quality and functionality meet standards and requirements Mentor junior team members Interact with Product Development Teams, Customers, Solution Providers, and cross-functional teams as needed Apply SDLC principles and methodologies like Lean/Agile/XP, CI, software and product security, scalability, and testing techniques Provide maintenance of power systems application functionality, including code fixes, creating tools for model conversion, documentation, and user interfaces Support marketing efforts for proposals and demonstrations to potential customers Basic Qualification Ph. D. or Master's degree in Electrical Power Systems with thesis or related work in power systems 8 to 11 years of experience in development or project delivery, preferably in Power Systems Analysis, Security Constrained Unit Commitment and Economic Dispatch using Mixed Integer Programming (MIP)/Optimization, or Applied Mathematics and Operations Research Desired Characteristics Continuous improvement mindset; drives change initiatives and process improvements Highly organized and efficient; adept at prioritizing and executing tasks Experience in the power systems domain Proficiency in testing and test automation Strong knowledge of source control management, particularly GitHub Demonstrated ability to learn new development practices, languages, and tools Self-motivated; able to synthesize information from diverse sources Mentors newer team members in alignment with business objectives Continuously measures the completion rate of personal deliverables and compares them to the scheduled commitments Transparent in problem-solving approaches and options; determines fair outcomes with shared trade-offs Capable of defining requirements and collaborating on solutions using technical expertise and a network of experts Effective communication style for engaging with customers and cross-functional teams; utilizes product knowledge to mitigate risks and drive outcomes Strong verbal, written, and interpersonal communication skills; able to produce professional and technical reports and conduct presentations Innovates and integrates new processes or technologies to add significant value; advises on change cost versus benefits and learns new solutions to address complex problems

The role entails advanced software development for Power Systems Applications, with a focus on delivering specific functionalities to meet corporate project and product objectives. Responsibilities include collaborating with team working with Electric Utilities or Independent System Operators (ISOs) and Transmission and Distribution System Operators to develop functional software specifications, followed by designing, coding, testing, integration, application tuning, and delivery. Job Description Roles and Responsibilities As a team member of the Software Center of Excellence, exemplifying high-quality development, testing, and delivery practices Responsible for enhancing, evolving, and supporting high-availability Electricity Energy Market Management System (MMS) Responsible for development, testing, integration, and tuning of advanced Power Systems Application software to fulfill project and product commitments Develop and evolve software in a dynamic and agile environment using the latest technologies and infrastructure Provide domain knowledge and/or technical support to a team of electricity markets application software engineers Understand customers' needs and focus throughout the project lifecycle to ensure software quality and functionality meet standards and requirements Interact with Product Development Teams, Customers, Solution Providers, and cross-functional teams as needed Apply SDLC principles and methodologies like Lean/Agile/XP, CI, software and product security, scalability, and testing techniques Provide maintenance of power systems application functionality, including code fixes, creating tools for model conversion, documentation, and user interfaces Basic Qualification Master's degree in Electrical Power Systems with thesis or related work in power systems 3 to 5 years of experience in development or project delivery, preferably in Power Systems Analysis, Security Constrained Unit Commitment and Economic Dispatch using Mixed Integer Programming (MIP)/Optimization, or Applied Mathematics and Operations Research Desired Characteristics Continuous improvement mindset; drives change initiatives and process improvements Highly organized and efficient; adept at prioritizing and executing tasks Experience in the power systems domain Proficiency in testing and test automation Experience in programming skills such as C++ or Java or other related language, as required. Knowledge on Perl, PowerShell and SQL (MSSQL and/or T-SQL) scripting languages. Good understanding of database operation Strong knowledge of source control management, particularly GitHub Demonstrated ability to learn new development practices, languages, and tools Self-motivated; able to synthesize information from diverse sources Continuously measures the completion rate of personal deliverables and compares them to the scheduled commitments Transparent in problem-solving approaches and options; determines fair outcomes with shared trade-offs Capable of defining requirements and collaborating on solutions using technical expertise and a network of experts Effective communication style for engaging with customers and cross-functional teams; utilizes product knowledge to mitigate risks and drive outcomes Strong verbal, written, and interpersonal communication skills; able to produce professional and technical reports and conduct presentations Innovates and integrates new processes or technologies to add significant value; advises on change cost versus benefits and learns new solutions to address complex problems

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Job Description: Senior Data Scientist Role Overview: We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 4 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role. Responsibilities: Your technical responsibilities: Contribute to the design and implementation of state-of-the-art AI solutions. Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, Agentic Framework to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus. Minimum 4 years of experience in Data Science and Machine Learning. In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements. Good to Have Skills: Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models Utilize optimization tools and techniques, including MIP (Mixed Integer Programming. Deep knowledge of classical AIML (regression, classification, time series, clustering) Drive DevOps and MLOps practices, covering CI/CD and monitoring of AI models. Implement CI/CD pipelines for streamlined model deployment and scaling processes. Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. Implement monitoring and logging tools to ensure AI model performance and reliability. Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

Job Summary: We are seeking a proactive and detail-oriented Data Scientist to join our team and contribute to the development of intelligent AI-driven production scheduling solutions. This role is ideal for candidates passionate about applying machine learning, optimization techniques, and operational data analysis to enhance decision-making and drive efficiency in manufacturing or process industries. You will play a key role in designing, developing, and deploying smart scheduling algorithms integrated with real-world constraints like machine availability, workforce planning, shift cycles, material flow, and due dates. Experience: 1 Year Responsibilities: 1. AI-Based Scheduling Algorithm Development Develop and refine scheduling models using: Constraint Programming Mixed Integer Programming (MIP) Metaheuristic Algorithms (e.g., Genetic Algorithm, Ant Colony, Simulated Annealing) Reinforcement Learning or Deep Q-Learning Translate shop floor constraints (machines, manpower, sequence dependencies, changeovers) into mathematical models. Create simulation environments to test scheduling models under different scenarios. 2. Data Exploration & Feature Engineering Analyze structured and semi-structured production data from MES, SCADA, ERP, and other sources. Build pipelines for data preprocessing, normalization, and handling missing values. Perform feature engineering to capture important relationships like setup times, cycle duration, and bottlenecks. 3. Model Validation & Deployment Use statistical metrics and domain KPIs (e.g., throughput, utilization, makespan, WIP) to validate scheduling outcomes. Deploy solutions using APIs, dashboards (Streamlit, Dash), or via integration with existing production systems. Support ongoing maintenance, updates, and performance tuning of deployed models. 4. Collaboration & Stakeholder Engagement Work closely with production managers, planners, and domain experts to understand real-world constraints and validate model results. Document solution approaches, model assumptions, and provide technical training to stakeholders. Qualifications: Bachelor’s or Master’s degree in: Data Science, Computer Science, Industrial Engineering, Operations Research, Applied Mathematics, or equivalent. Minimum 1 year of experience in data science roles with exposure to: AI/ML pipelines, predictive modelling, Optimization techniques or industrial scheduling Proficiency in Python, especially with: pandas, numpy, scikit-learn ortools, pulp, cvxpy or other optimization libraries, matplotlib, plotly for visualization Solid understanding of: Production planning & control processes (dispatching rules, job-shop scheduling, etc.), Machine Learning fundamentals (regression, classification, clustering) Familiarity with version control (Git), Jupyter/VSCode environments, and CI/CD principles Preferred (Nice-to-Have) Skills: Experience with: Time-series analysis, sensor data, or anomaly detection, Manufacturing execution systems (MES), SCADA, PLC logs, or OPC UA data, Simulation tools (SimPy, Arena, FlexSim) or digital twin technologies Exposure to containerization (Docker) and model deployment (FastAPI, Flask) Understanding of lean manufacturing principles, Theory of Constraints, or Six Sigma Soft Skills: Strong problem-solving mindset with ability to balance technical depth and business context. Excellent communication and storytelling skills to convey insights to both technical and non-technical stakeholders. Eagerness to learn new tools, technologies, and domain knowledge.

Position Overview Job title: Debt Strategic Analytics Corporate Title: VP Location: Mumbai, India Role Description Deutsche CIB Centre Pvt Ltd is Deutsche bank’s global platform for front-office & aligned functions to create value by utilizing non-traditional locations, exceptional talent, and a collaborative culture. This branch of Deutsche Bank Group company is looking for extremely bright candidates for the role of Debt Strategic Analytics (Strats). The candidate is required to work in close collaboration with London/Singapore teams on various quantitative and regulatory driven projects. Candidate is required to understand the business problem, gather information required for the implementation and provide an end-to-end optimized solution on a scalable platform. Implementation of the project needs to be done in Python and C++ programming language. Candidate should possess excellent English communication skills to coordinate and communicate effectively with various stakeholders spread across the globe. What We’ll Offer You As part of our flexible scheme, here are just some of the benefits that you’ll enjoy Best in class leave policy Gender neutral parental leaves 100% reimbursement under childcare assistance benefit (gender neutral) Flexible working arrangements Employee Assistance Program for you and your family members Comprehensive Hospitalization Insurance for you and your dependents Accident and Term life Insurance Your Key Responsibilities The Quantitative Strategist (Quant Strat) is responsible for designing, developing and implementing through analytical (quantitative) and direct coding (e.g., via C++; Python or any other relevant application), quantitative strategic models, risk management (credit risk, market risk, anti-financial crime etc.) and pricing solutions to meet business & control needs and drive respective strategies or regulatory adherence. Some responsibilities for this role include, but not limited to: Work with Capital and Liquidity Management colleagues in Treasury to develop a framework to optimize funding for the bank, manage asset and liability mismatches in the liquidity pool and bring more transparency into the process. Development of complex processes, framework or risk analysis as well as improvements specially focused on Liquidity Risk. Implement, enhance and maintain existing framework to measure market risks across the bank from Treasury perspective. Remediation of regulatory as well as external and internal findings against any existing risk model. Build quant driven tools and products for front-office and control functions. Coordinate and gather information from various stakeholders for deeper understanding of the business. Develop and design tables and databases required for storage of the data. Design an automated solution which is optimized and scalable. Your Skills And Experience Strong programming skills in C++ and Python preferably in financial industry. Relevant experience of at least 8 years in Banking or Software Development. At least 3+ year experience with relational database design (oracle, mysql). Strong understanding of Data Structures & Algorithms, memory optimization etc. Good quantitative skills in Probability, Calculus, and Linear Algebra. Experience with applied econometrics (Hypothesis testing, PCA, Linear/Non-Linear Regression etc.) is a plus. Knowledge of applied linear/Integer linear programming, dynamic programming & greedy algorithms is a plus. Relevant experience in some of financial products like Bonds, Swaps, Cross Currency Swaps, Loans & Deposits is a plus. Strong communication skills and presentation ability with attention to detail. Good problem-solving instincts and strong analytical skills. Strong educational background in Engineering/Science, preferably from top tier colleges in India. How We’ll Support You Training and development to help you excel in your career. Flexible working to assist you balance your personal priorities. Coaching and support from experts in your team. A culture of continuous learning to aid progression. A range of flexible benefits that you can tailor to suit your needs. About Us And Our Teams Please visit our company website for further information: https://www.db.com/company/company.htm We strive for a culture in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively. Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group. We welcome applications from all people and promote a positive, fair and inclusive work environment.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Job Description: Senior AI Engineer (Tech Lead) Role Overview: We are seeking a highly skilled and experienced Senior AI Engineers with a minimum of 4 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role. Responsibilities: Your technical responsibilities: Contribute to the design and implementation of state-of-the-art AI solutions. Leading a team of 4-6 developers Assist in the development and implementation of AI models and systems, leveraging techniques such as Large Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, Agentic Framework to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Minimum 4 years of experience in Python, Data Science, Machine Learning, OCR and document intelligence Experience in leading a team of 4-6 developers Demonstrated ability to conceptualize technical solutions, apply accurate estimation techniques, and effectively engage with customer stakeholders In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Strong knowledge of Python frameworks such as Django, Flask, or FastAPI. Experience with RESTful API design and development. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements. Good to Have Skills: Understanding of agentic AI concepts and frameworks Proficiency in designing or interacting with agent-based AI architectures Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems. Utilize optimization tools and techniques, including MIP (Mixed Integer Programming). Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models. Implement CI/CD pipelines for streamlined model deployment and scaling processes. Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. Implement monitoring and logging tools to ensure AI model performance and reliability. Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. AI Engineer Role Overview: We are seeking a highly skilled and experienced AI Engineers with a minimum of 2 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role. Your technical responsibilities: Assist in the development and implementation of AI models and systems, leveraging techniques such as Large Language Models (LLMs) and generative AI. Design, develop, and maintain efficient, reusable, and reliable Python code Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, Agentic Framework to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Write unit tests and conduct code reviews to ensure high-quality, bug-free software. Troubleshoot and debug applications to optimize performance and fix issues. Work with databases (SQL, NoSQL) and integrate third-party APIs. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Minimum 2 years of experience in Python, Data Science, Machine Learning, OCR and document intelligence In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Strong knowledge of Python frameworks such as Django, Flask, or FastAPI. Experience with RESTful API design and development. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Good to Have Skills: Understanding of agentic AI concepts and frameworks Proficiency in designing or interacting with agent-based AI architectures Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems. Utilize optimization tools and techniques, including MIP (Mixed Integer Programming). Implement CI/CD pipelines for streamlined model deployment and scaling processes. Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. Implement monitoring and logging tools to ensure AI model performance and reliability. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Senior Data Scientist Role Overview: We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 4 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role. Responsibilities: Your technical responsibilities: Contribute to the design and implementation of state-of-the-art AI solutions. Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, Agentic Framework to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus. Minimum 4 years of experience in Data Science and Machine Learning. In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements. Good to Have Skills: Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models Utilize optimization tools and techniques, including MIP (Mixed Integer Programming. Deep knowledge of classical AIML (regression, classification, time series, clustering) Drive DevOps and MLOps practices, covering CI/CD and monitoring of AI models. Implement CI/CD pipelines for streamlined model deployment and scaling processes. Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. Implement monitoring and logging tools to ensure AI model performance and reliability. Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – Data and Analytics (D&A) – Senior – Senior Data Scientist Role Overview: We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 3 - 7 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role. Responsibilities: Your technical responsibilities: Contribute to the design and implementation of state-of-the-art AI solutions. Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus. Minimum 3-7 years of experience in Data Science and Machine Learning. In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements. Good to Have Skills: Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems. Utilize optimization tools and techniques, including MIP (Mixed Integer Programming). Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models. Implement CI/CD pipelines for streamlined model deployment and scaling processes. Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. Implement monitoring and logging tools to ensure AI model performance and reliability. Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – Data and Analytics (D&A) – Senior – Senior Data Scientist Role Overview: We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 3 - 7 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role. Responsibilities: Your technical responsibilities: Contribute to the design and implementation of state-of-the-art AI solutions. Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus. Minimum 3-7 years of experience in Data Science and Machine Learning. In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements. Good to Have Skills: Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems. Utilize optimization tools and techniques, including MIP (Mixed Integer Programming). Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models. Implement CI/CD pipelines for streamlined model deployment and scaling processes. Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. Implement monitoring and logging tools to ensure AI model performance and reliability. Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – Data and Analytics (D&A) – Senior – Senior Data Scientist Role Overview: We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 3 - 7 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role. Responsibilities: Your technical responsibilities: Contribute to the design and implementation of state-of-the-art AI solutions. Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus. Minimum 3-7 years of experience in Data Science and Machine Learning. In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements. Good to Have Skills: Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems. Utilize optimization tools and techniques, including MIP (Mixed Integer Programming). Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models. Implement CI/CD pipelines for streamlined model deployment and scaling processes. Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. Implement monitoring and logging tools to ensure AI model performance and reliability. Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

Company Description: At AnjX, we believe that every decision impacts not only business outcomes but also the world around us. AnjX is dedicated to transforming global supply chains through AI-driven solutions that enhance efficiency and decision-making. By leveraging cutting-edge technology, AnjX helps businesses streamline processes, optimize resources, and ensure reliable planning. With a focus on demand forecasting, production planning, and inventory optimization, AnjX empowers enterprises to thrive in a rapidly evolving marketplace. Our mission is to create platforms that drive unprecedented speed, reliability, and transparency, helping organizations reduce their environmental impact while achieving operational excellence. We are seeking a dynamic and motivated candidates to join our team for a paid internship ( ₹8000/month) and contribute to the growth of AnjX. Roles and Responsibilities: Assist in developing mathematical models for optimizing production planning and inventory management. Work with the product team to define constraints, objectives, and optimization goals. Perform simulations and scenario analysis to evaluate different planning strategies. Help implement linear programming and mixed-integer programming models in collaboration with the software engineering team. Provide research support for new optimization techniques or approaches that could enhance the software. Skills Required: Understanding of linear programming, optimization techniques, and operations research concepts. Familiarity with tools like Python, MATLAB, R or Gurobi for optimization. Strong mathematical and problem-solving skills. Ability to work with cross-functional teams and translate business problems into mathematical models. Knowledge of supply chain and production planning is a plus. Background in mathematics, engineering, or operations research is preferred. On-site work at Chennai Office.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – Data and Analytics (D&A) – Senior – Senior Data Scientist Role Overview: We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 3 - 7 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role. Responsibilities: Your technical responsibilities: Contribute to the design and implementation of state-of-the-art AI solutions. Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus. Minimum 3-7 years of experience in Data Science and Machine Learning. In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements. Good to Have Skills: Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems. Utilize optimization tools and techniques, including MIP (Mixed Integer Programming). Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models. Implement CI/CD pipelines for streamlined model deployment and scaling processes. Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. Implement monitoring and logging tools to ensure AI model performance and reliability. Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

About Team The Myntra Data Science team is at the forefront of innovation, delivering cutting-edge solutions that drive significant revenue and enhance customer experiences across various touchpoints. Every quarter, our models impact millions of customers, leveraging real-time, near-real-time, and offline solutions with diverse latency requirements. These models are built on massive datasets, allowing for deep learning and growth opportunities within a rapidly expanding organization. By joining our team, you'll gain hands-on experience with an extensive e-commerce platform, learning to develop models that handle millions of requests per second with sub-second latency. We take pride in deploying solutions that not only utilize state-of-the-art machine learning techniques—such as graph neural networks, diffusion models, transformers, representation learning, optimization methods, and Bayesian modeling—but also contribute to the research community with multiple peer-reviewed publications. Roles and Responsibilities Design, develop, and deploy advanced machine learning models and algorithms for Forecasting, Operations Research, and Time Series applications. Build and implement scalable solutions for supply chain optimization, demand forecasting, pricing, and trend prediction. Develop efficient forecasting models leveraging traditional and deep learning-based time series analysis techniques. Utilize optimization techniques for large-scale nonlinear and integer programming problems. Hands-on experience with optimization solvers like CPLEX, Gurobi, COIN-OR, or similar tools. Collaborate with Product, Engineering, and Business teams to understand challenges and integrate ML solutions effectively. Maintain and optimize machine learning pipelines, including data cleaning, feature extraction, and model training. Implement CI/CD pipelines for automated testing, deployment, and integration of machine learning models. Work closely with the Data Platforms team to collect, process, and analyze data crucial for model development. Stay up to date with the latest advancements in machine learning, forecasting, and optimization techniques, sharing insights with the team. Qualifications & Experience Experience with a Bachelor’s degree in Statistics, Operations Research, Mathematics, Computer Science, or a related field. Strong foundation in data structures, algorithms, and efficient processing of large datasets. Proficiency in Python for data science and machine learning applications. Experience in developing and deploying forecasting and time series models. Knowledge of ML frameworks such as TensorFlow, PyTorch, and Scikit-learn. Hands-on experience with optimization solvers and algorithms for supply chain and logistics problems. Strong problem-solving skills with a focus on applying OR techniques to real-world business challenges. Good to have research publications in Machine Learning, Forecasting, or Operations Research. Familiarity with cloud computing services (AWS, Google Cloud) and distributed systems. Strong communication skills with the ability to work independently and collaboratively in a team environment. Nice to Have Experience with Generative AI and Large Language Models (LLMs). Knowledge of ML orchestration tools such as Airflow, Kubeflow, and MLflow. Exposure to NLP and Computer Vision applications in an e-commerce setting. Understanding of ethical considerations in AI, including bias, fairness, and privacy. Exceptional candidates are encouraged to apply, even if they don’t meet every listed qualification. We value potential and a strong willingness to learn.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – Data and Analytics (D&A) – Senior – Senior Data Scientist Role Overview: We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 3 - 7 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role. Responsibilities: Your technical responsibilities: Contribute to the design and implementation of state-of-the-art AI solutions. Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus. Minimum 3-7 years of experience in Data Science and Machine Learning. In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements. Good to Have Skills: Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems. Utilize optimization tools and techniques, including MIP (Mixed Integer Programming). Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models. Implement CI/CD pipelines for streamlined model deployment and scaling processes. Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. Implement monitoring and logging tools to ensure AI model performance and reliability. Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

Patiënt Bezoeker Professional Zorgaanbod Campussen Het Jan Yperman Ziekenhuis is met meer dan 1400 medewerkers, 140 artsen en 532 bedden modern, jong en dynamisch. Een ziekenhuis waar de patiënt in het streven naar de beste zorg centraal staat en zeer veel aandacht aan kwalitatief hoogstaande geneeskunde wordt besteed. Als vernieuwend ziekenhuis investeren we in een stimulerende werkomgeving en teamwerk. We reiken volop kansen aan voor persoonlijke en professionele groei, met de focus op continue ontwikkeling en opleiding. Aan de slag als verpleegkundige in de polikliniek van Diksmuide en Poperinge Wil jij werken in een warme en professionele zorgomgeving? Op de poliklinieken van onze perifere campussen in Diksmuide en Poperinge staan we elke dag klaar om patiënten kwaliteitsvolle zorg te bieden. Deskundig, zorgzaam en met plezier. De werksfeer is open, informeel en collegiaal. Samen vormen we het visitekaartje van de poli. Jij zorgt ervoor dat patiënten zich welkom voelen en dat alles ook administratief vlot verloopt. Je komt terecht in een hecht team van een dertigtal artsen en zes verpleegkundigen. Ben jij net zo enthousiast als wij? Solliciteer dan snel, we maken graag kennis met je! Functie-inhoud Als verpleegkundige van deze poliklinieken coördineer en realiseer je medisch-technische onderzoeken en behandelingen in samenwerking met de betrokken artsen om een adequate en snelle diagnose en/of behandeling toe te laten. Jouw Takenpakket Omvat Onthalen, begeleiden en informeren van de patiënten en eventueel familie of begeleiders over het verloop van de medisch-technische onderzoeken of behandelingen om hun medewerking te bekomen, hen gerust te stellen en de onderzoeken of behandelingen op een optimale wijze uit te voeren. Plaatsen van de patiënt in een optimale positie zodat er precieze resultaten worden verkregen en uitvoeren van de onderzoeken, autonoom of in samenwerking met de arts. Bijstaan van de artsen in de uitvoering van de specifieke technische handelingen zoals echografie, punctie, biopsie, … Verstrekken van de nodige nazorg aan de patiënten, hen observeren en hun gezondheidstoestand controleren, detecteren van eventuele moeilijkheden en anticiperen op crisissituaties. Verstrekken van uitleg aan de patiënten en hun naasten over de opvolging van de raadpleging, hen informeren en hen op vraag van de arts naar andere medisch-technische afdelingen verwijzen. Uitvoeren van de logistieke taken voor en na de uitvoering van medisch-technische onderzoeken of behandelingen, zoals het klaarmaken van het lokaal voor de geplande onderzoeken of behandelingen, instrumenten klaarleggen, reinigen en desinfecteren van het materiaal na elk onderzoek en het lokaal opruimen, ervoor zorgen dat het te steriliseren materiaal naar de sterilisatieafdeling gaat. Verzamelen, evalueren en registreren van de gegevens van de patiënten om het onderzoek en gebruikte materiaal te kunnen factureren. Uitvoeren van het klein onderhoud van het materiaal, apparaten en producten en uitvoeren van de kwaliteitscontroles om de precisie van de gegevens te verbeteren en de veiligheid van de patiënten te waarborgen. Functieprofiel Je bent bachelor of gegradueerde in de Verpleegkunde. Je hebt kennis van de medisch-technische processen en de protocollen van onderzoeken en behandelingen of je vindt het een uitdaging om je hierin te verdiepen. Je bent leergierig en ziet het als een kans om vertrouwd te raken met de werking van de polikliniek en om voortdurend bij te leren in je job. Je bent bereid om administratieve taken op te nemen (maken van vervolgafspraken, bijhouden databank). Je kan met de specifieke informaticatoepassingen werken. Kennis van KWS is een meerwaarde of bent hierin een vlotte leerling. Je beschikt over een grote portie aan inlevingsvermogen. Je bent open, respectvol en integer en klantvriendelijkheid zit in je DNA. Je kan georganiseerd en accuraat handelen en daarbij je zaken terdege afwerken. Je kan je, zeker mondeling, vlot in het Nederlands en Frans uitdrukken. Je fungeert als voorbeeld voor kwaliteitsgerichtheid en professionaliteit. Je zoekt actief naar mogelijkheden voor het vergroten van de eigen deskundigheid en verdere professionele en persoonlijke ontwikkeling. Wij bieden je Een contract van onbepaalde duur. Of opname in de werfreserve. Een deeltijdse betrekking van 30 uur per week. Een flexibele inzet op de perifere campussen Diksmuide en Poperinge, met Poperinge als jouw hoofdlocatie of prioritaire campus. Een wisselend uurrooster in de week met shiften tussen 7u30 en 19u. Een werkregime zonder weekendwerk. Verloning volgens IFIC 14 of 14b (code 6177). Verlofregeling: 24 verlofdagen voor een voltijdse tewerkstelling (pro rata jobtime). On-the-job inwerking. Tal van voordelen zoals fietsleasing, gratis griepvaccin, hospitalisatieverzekering, kortingen via Benefits@work, Bringme box en een betaalbaar personeelsrestaurant. Tussenkomst woon-werkverkeer (o.a. fietsvergoeding). Kinderopvang in de vakantieperiodes. Jobtype Bediende Contracttype Onbepaalde duur Werkregime Deeltijds Solliciteren kan tot 10/08/2025 Meer Info Via Magali Vilain, adjunct-hoofdverpleegkundige: 057 35 72 57. Justine Wybaillie, verpleegkundige-diensthoofd: 057 35 70 65. Veel succes! Solliciteer hier online Jan Yperman Ziekenhuis Briekestraat 12 8900 Ieper 057 35 35 35 info@yperman.net Ondernemingsnummer: BE 0462.915.078 Rechtspersonenregister (RPR) Gent, afdeling Ieper Alle campussen

Role: Data Scientist Experience : 8year+ Location : Ahmedabad /Hyderabad We are seeking a Data Scientist to develop and implement advanced predictive models and optimization solutions. The ideal candidate will have expertise in predictive modelling, integer programming, Python development, and cloud-based data processing. This role will involve working with large datasets, solving complex and managing cloud infrastructure for scalable solutions. Key Responsibilities: Develop and implement models using statistical methods (e.g., Bayesian models). Solve optimization problems such as bin packing, TSP, and clustering using integer programming. Develop Python-based solutions using Git/Poetry for code and library management. Work with data processing libraries such as Pandas, Polars, and others. Deploy and manage data pipelines on Databricks and Azure Blob Storage. Monitor and troubleshoot pipelines, logs, and cloud resources. Implement DevOps best practices (nice-to-have) for automation and CI/CD workflows. Utilize Power Apps/Power Automate for workflow automation and business process improvement. Ensure cloud cost optimization and performance tuning for scalable architectures. Required Skills & Qualifications: Strong experience in predictive modeling and statistical techniques (Bayesian modeling preferred). Hands-on experience with integer programming and clustering methods. Proficiency in Python, including experience with Git/Poetry for code and dependency management. Expertise in data processing libraries such as Pandas, Polars, or equivalent. Familiarity with Azure cloud services, Databricks, and Azure Blob Storage. Ability to read and analyze logs for debugging and performance monitoring. Experience with cloud management and optimizing resources. Knowledge of monitoring pipelines and troubleshooting issues. Strong problem-solving skills and ability to work with large-scale datasets. Preferred Qualifications: Exposure to DevOps practices, including CI/CD pipelines and automation. Familiarity with Power Apps/Power Automate for process automation. Strong background in cloud cost management and performance tuning

Patiënt Bezoeker Professional Zorgaanbod Campussen Het Jan Yperman Ziekenhuis is met meer dan 1400 medewerkers, 140 artsen en 532 bedden modern, jong en dynamisch. Een ziekenhuis waar de patiënt in het streven naar de beste zorg centraal staat en zeer veel aandacht aan kwalitatief hoogstaande geneeskunde wordt besteed. Als vernieuwend ziekenhuis investeren we in een stimulerende werkomgeving en teamwerk. We reiken volop kansen aan voor persoonlijke en professionele groei, met de focus op continue ontwikkeling en opleiding. Word jij onze nieuwe apotheekassistent? Samen met artsen, apothekers, verpleegkundigen en vele andere collega’s draag je bij aan de best mogelijke zorg voor onze patiënten. We investeren volop in vernieuwing en automatisering. Dankzij twee geavanceerde robots voor de verdeling van geneesmiddelen zitten we helemaal op kruissnelheid wat technologie betreft. Binnenkort zetten we een volgende stap voorwaarts: we bouwen onze eigen cleanroom en houden hiermee de bereiding van geneesmiddelen zelf in handen. Met deze ambitieuze ontwikkeling willen we nog beter inspelen op de specifieke noden van onze patiënten en zetten we ons elke dag in om de hoogste kwaliteitsnormen te behalen. Om deze uitdaging waar te maken, zijn we op zoek naar een gedreven en geëngageerde collega die samen met ons wil bouwen aan dit vernieuwende project. Ons apotheekteam bestaat uit 9 ziekenhuisapothekers en 15 apotheekmedewerkers. Functie-inhoud Als apotheekassistent ben je voornamelijk verantwoordelijk voor de bereiding van geneesmiddelen, waaronder de steriele, cytostatica en magistrale bereidingen. Je zal eveneens een belangrijke rol spelen in de uitbouw van de nieuwe cleanroom. Je draagt met jouw inzet bij aan een veilige en efficiënte werkomgeving. Functieprofiel Je bent farmaceutisch technisch assistent. Ervaring met het bereiden van geneesmiddelen in een cleanroom biedt toegevoegde waarde, zonder dat dit daarom een must hoeft te zijn. Je kan met de specifieke informaticatoepassingen werken. Kennis van Word en Excel is een meerwaarde of je bent hierin een vlotte leerling. Je bent open, respectvol en integer en klantvriendelijkheid zit in je DNA. Je vindt vlot je weg in een dynamisch team. Je hebt geen problemen om de nodige flexibiliteit aan de dag te leggen. Je kan op georganiseerde en nauwgezette wijze je taken afwerken. Je fungeert als voorbeeld voor kwaliteitsgerichtheid en professionaliteit. Je zoekt actief naar mogelijkheden voor het vergroten van de eigen deskundigheid en verdere professionele en persoonlijke ontwikkeling. Wij bieden je Een contract van onbepaalde duur. Of opname in de werfreserve. Een voltijdse betrekking. Een wisselend uurrooster met shiften tussen 8u en 18u. Een werkregime met beperkt weekendwerk: 1 weekend per 3 maanden werken. Verloning volgens IFIC 11 (code 3072). Op termijn kan dit evolueren naar IFIC 13. Relevante toeslaguren. Verlofregeling: 24 verlofdagen voor een voltijdse tewerkstelling (pro rata jobtime). 40 uur werken in een 38 urenweekstelsel, wat in 12 extra compensatiedagen op jaarbasis resulteert. On-the-job inwerking: we voorzien een grondige opleiding en begeleiding zodat je stap voor stap kan groeien in je rol. Tal van voordelen zoals fietsleasing, gratis griepvaccin, hospitalisatieverzekering, kortingen via Benefits@work, Bringme box en een betaalbaar personeelsrestaurant. Woon-werkverkeer (fietsvergoeding). Kinderopvang in de vakantieperiodes. Een warm team met toffe collega’s die voor elkaar klaarstaan. Jobtype Bediende Contracttype Onbepaalde duur Werkregime Voltijds Solliciteren kan tot 03/08/2025 Meer Info Via Eveline Lauwers, apotheker-titularis: 057 35 65 52. Veel succes! Solliciteer hier online Jan Yperman Ziekenhuis Briekestraat 12 8900 Ieper 057 35 35 35 info@yperman.net Ondernemingsnummer: BE 0462.915.078 Rechtspersonenregister (RPR) Gent, afdeling Ieper Alle campussen

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Job Description: Senior AI Engineer (Tech Lead) Role Overview: We are seeking a highly skilled and experienced Senior AI Engineers with a minimum of 4 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role. Responsibilities: Your technical responsibilities: Contribute to the design and implementation of state-of-the-art AI solutions. Leading a team of 4-6 developers Assist in the development and implementation of AI models and systems, leveraging techniques such as Large Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, Agentic Framework to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Minimum 4 years of experience in Python, Data Science, Machine Learning, OCR and document intelligence Experience in leading a team of 4-6 developers Demonstrated ability to conceptualize technical solutions, apply accurate estimation techniques, and effectively engage with customer stakeholders In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Strong knowledge of Python frameworks such as Django, Flask, or FastAPI. Experience with RESTful API design and development. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements. Good to Have Skills: Understanding of agentic AI concepts and frameworks Proficiency in designing or interacting with agent-based AI architectures Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems. Utilize optimization tools and techniques, including MIP (Mixed Integer Programming). Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models. Implement CI/CD pipelines for streamlined model deployment and scaling processes. Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. Implement monitoring and logging tools to ensure AI model performance and reliability. Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

Job Description Summary The role entails advanced software development for Power Systems Applications, with a focus on delivering specific functionalities to meet corporate project and product objectives. Responsibilities include collaborating with team working with Electric Utilities or Independent System Operators (ISOs) and Transmission and Distribution System Operators to develop functional software specifications, followed by designing, coding, testing, integration, application tuning, and delivery Job Description Roles and Responsibilities As a senior member of the Software Center of Excellence, exemplifying high-quality development, testing, and delivery practices. Responsible for enhancing, evolving, and supporting high-availability Electricity Energy Market Management System (MMS). Responsible for development, testing, integration, and tuning of advanced Power Systems Application software to fulfill project and product commitments. Develop and evolve software in a dynamic and agile environment using the latest technologies and infrastructure. Provide domain knowledge and/or technical leadership to a team of electricity markets application software engineers. Support in providing budget estimates for new project tasks to project leads and managers. Collaborate with customers throughout the project lifecycle to ensure software quality and functionality meet standards and requirements. Interact with Product Development Teams, Customers, Solution Providers, and cross-functional teams as needed. Apply SDLC principles and methodologies like Lean/Agile/XP, CI, software and product security, scalability, and testing techniques. Provide maintenance of power systems application functionality, including code fixes, creating tools for model conversion, documentation, and user interfaces. Support marketing efforts for proposals and demonstrations to potential customers. Basic Qualification Master’s degree in Electrical Power Systems with thesis or related work in power systems 5 to 8 years of experience in development or project delivery, preferably in Power Systems Analysis, Security Constrained Unit Commitment and Economic Dispatch using Mixed Integer Programming (MIP)/Optimization, or Applied Mathematics and Operations Research. Desired Characteristics Continuous improvement mindset; drives change initiatives and process improvements Highly organized and efficient; adept at prioritizing and executing tasks. Experience in the power systems domain. Proficiency in testing and test automation. Strong knowledge of source control management, particularly GitHub. Demonstrated ability to learn new development practices, languages, and tools. Self-motivated; able to synthesize information from diverse sources. Continuously measures the completion rate of personal deliverables and compares them to the scheduled commitments. Transparent in problem-solving approaches and options; determines fair outcomes with shared trade-offs. Capable of defining requirements and collaborating on solutions using technical expertise and a network of experts. Effective communication style for engaging with customers and cross-functional teams; utilizes product knowledge to mitigate risks and drive outcomes. Strong verbal, written, and interpersonal communication skills; able to produce professional and technical reports and conduct presentations. Innovates and integrates new processes or technologies to add significant value; advises on change cost versus benefits and learns new solutions to address complex problems Additional Information Relocation Assistance Provided: Yes