Designation: - ML / MLOPs Engineer Location: - Noida (Sector- 132) Key Responsibilities: • Model Development & Algorithm Optimization : Design, implement, and optimize ML models and algorithms using libraries and frameworks such as TensorFlow , PyTorch , and scikit-learn to solve complex business problems. • Training & Evaluation : Train and evaluate models using historical data, ensuring accuracy, scalability, and efficiency while fine-tuning hyperparameters. • Data Preprocessing & Cleaning : Clean, preprocess, and transform raw data into a suitable format for model training and evaluation, applying industry best practices to ensure data quality. • Feature Engineering : Conduct feature engineering to extract meaningful features from data that enhance model performance and improve predictive capabilities. • Model Deployment & Pipelines : Build end-to-end pipelines and workflows for deploying machine learning models into production environments, leveraging Azure Machine Learning and containerization technologies like Docker and Kubernetes . • Production Deployment : Develop and deploy machine learning models to production environments, ensuring scalability and reliability using tools such as Azure Kubernetes Service (AKS) . • End-to-End ML Lifecycle Automation : Automate the end-to-end machine learning lifecycle, including data ingestion, model training, deployment, and monitoring, ensuring seamless operations and faster model iteration. • Performance Optimization : Monitor and improve inference speed and latency to meet real- time processing requirements, ensuring efficient and scalable solutions. • NLP, CV, GenAI Programming : Work on machine learning projects involving Natural Language Processing (NLP) , Computer Vision (CV) , and Generative AI (GenAI) , applying state-of-the-art techniques and frameworks to improve model performance. • Collaboration & CI/CD Integration : Collaborate with data scientists and engineers to integrate ML models into production workflows, building and maintaining continuous integration/continuous deployment (CI/CD) pipelines using tools like Azure DevOps , Git , and Jenkins . • Monitoring & Optimization : Continuously monitor the performance of deployed models, adjusting parameters and optimizing algorithms to improve accuracy and efficiency. • Security & Compliance : Ensure all machine learning models and processes adhere to industry security standards and compliance protocols , such as GDPR and HIPAA . • Documentation & Reporting : Document machine learning processes, models, and results to ensure reproducibility and effective communication with stakeholders. Required Qualifications: • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field. • 3+ years of experience in machine learning operations (MLOps), cloud engineering, or similar roles. • Proficiency in Python , with hands-on experience using libraries such as TensorFlow , PyTorch , scikit-learn , Pandas , and NumPy . • Strong experience with Azure Machine Learning services, including Azure ML Studio , Azure Databricks , and Azure Kubernetes Service (AKS) . • Knowledge and experience in building end-to-end ML pipelines, deploying models, and automating the machine learning lifecycle. • Expertise in Docker , Kubernetes , and container orchestration for deploying machine learning models at scale. • Experience in data engineering practices and familiarity with cloud storage solutions like Azure Blob Storage and Azure Data Lake . • Strong understanding of NLP , CV , or GenAI programming, along with the ability to apply these techniques to real-world business problems. • Experience with Git , Azure DevOps , or similar tools to manage version control and CI/CD pipelines. • Solid experience in machine learning algorithms , model training , evaluation , and hyperparameter tuning Show more Show less

Company: Qualcomm India Private Limited Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: More details below: Join the exciting Generative AI team at Qualcomm focused on integrating cutting edge GenAI models on Qualcomm chipsets. The team uses Qualcomm chips’ extensive heterogeneous computing capabilities to allow inference of GenAI models on-device without a need for connection to the cloud. Our inference engine is designed to help developers run neural network models trained in a variety of frameworks on Snapdragon platforms at blazing speeds while still sipping the smallest amount of power. Utilize this power efficient hardware and Software stack to run Large Language Models (LLMs) and Large Vision Models (LVM) at near GPU speeds! Responsibilities: In this role, you will spearhead the development and commercialization of the Qualcomm AI Runtime (QAIRT) SDK on Qualcomm SoCs. As an AI inferencing expert, you'll push the limits of performance from large models. Your mastery in deploying large C/C++ software stacks using best practices will be essential. You'll stay on the cutting edge of GenAI advancements, understanding LLMs/Transformers and the nuances of edge-based GenAI deployment. Most importantly, your passion for the role of edge in AI's evolution will be your driving force. Minimum Qualifications: Bachelor’s degree in engineering, Computer Science, or related field and 10+ years of Systems Engineering or related work experience. OR Master’s degree in engineering, Computer Science, or related field and 9+ years of Systems Engineering or related work experience. Requirements: Strong understanding of Generative AI models – LLM, LVM, LMMs and building blocks (self-attention, cross attention, KV caching etc.) Floating-point, Fixed-point representations and Quantization concepts. Experience with optimizing algorithms for AI hardware accelerators (like CPU/GPU/NPU). Hands-on experience in C/C++ programming, Design Patterns and OS concepts. Excellent analytical and debugging skills. Exposure to shell scripts, python scripts, understanding of Linux/Windows systems and automation scripts/environment. Good communication skills, presentation skills and should manage his/her tasks independently. Ability to collaborate across a globally diverse team and multiple interests. Preferred Qualifications Strong understanding of SIMD processor architecture and system design. Proficiency in object-oriented software development and familiarity Familiarity with Linux and Windows environment Strong background in kernel development for SIMD architectures. Familiarity with frameworks like llama.cpp, MLX, and MLC is a plus. Good knowledge of PyTorch, TFLite, and ONNX Runtime is preferred. Experience with parallel computing systems and languages like OpenCL and CUDA is a plus Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. 2+ years of work experience with Programming Language such as C, C++, Java, Python, etc. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers. 3073180 Show more Show less

Role Overview As a Test Automation Lead at Dailoqa, you’ll architect and implement robust testing frameworks for both software and AI/ML systems. You’ll bridge the gap between traditional QA and AI-specific validation, ensuring seamless integration of automated testing into CI/CD pipelines while addressing unique challenges like model accuracy, GenAI output validation, and ethical AI compliance. Key Responsibilities Test Automation Strategy & Framework Design Design and implement scalable test automation frameworks for frontend (UI/UX) , backend APIs , and AI/ML model-serving endpoints using tools like Selenium, Playwright, Postman, or custom Python/Java solutions. Build GenAI-specific test suites for validating prompt outputs, LLM-based chat interfaces, RAG systems, and vector search accuracy. Develop performance testing strategies for AI pipelines (e.g., model inference latency, resource utilization). Continuous Testing & CI/CD Integration Establish and maintain continuous testing pipelines integrated with GitHub Actions, Jenkins, or GitLab CI/CD. Implement shift-left testing by embedding automated checks into development workflows (e.g., unit tests, contract testing). AI/ML Model Validation Collaborate with data scientists to test AI/ML models for accuracy , fairness , stability , and bias mitigation using tools like TensorFlow Model Analysis or MLflow. Validate model drift and retraining pipelines to ensure consistent performance in production. Quality Metrics & Reporting Define and track KPIs. Test coverage (code, data, scenarios) Defect leakage rate Automation ROI (time saved vs. maintenance effort) Model accuracy thresholds Report risks and quality trends to stakeholders in sprint reviews. Drive adoption of AI-specific testing tools (e.g., LangChain for LLM testing, Great Expectations for data validation). Soft Skills Strong problem-solving skills for balancing speed and quality in fast-paced AI development. Ability to communicate technical risks to non-technical stakeholders. Collaborative mindset to work with cross-functional teams (data scientists, ML engineers, DevOps). Requirements Technical Requirements Must-Have 5–8 years in test automation, with 2+ years validating AI/ML systems. Expertise in: Automation tools: Selenium, Playwright, Cypress, REST Assured, Locust/JMeter CI/CD: Jenkins, GitHub Actions, GitLab AI/ML testing: Model validation, drift detection, GenAI output evaluation Languages: Python, Java, or JavaScript Certifications: ISTQB Advanced, CAST, or equivalent. Experience with MLOps tools: MLflow, Kubeflow, TFX Familiarity with vector databases (Pinecone, Milvus) and RAG workflows. Strong programming/scripting experience in JavaScript, Python, Java, or similar Experience with API testing, UI testing, and automated pipelines Understanding of AI/ML model testing, output evaluation, and non-deterministic behavior validation Experience with testing AI chatbots, LLM responses, prompt engineering outcomes, or AI fairness/bias Familiarity with MLOps pipelines and automated validation of model performance in production Exposure to Agile/Scrum methodology and tools like Azure Boards Show more Show less

About the Open Position Join us as Cloud Engineer at Dailoqa , where you will be responsible for operationalizing cutting-edge machine learning and generative AI solutions, ensuring scalable, secure, and efficient deployment across infrastructure. You will work closely with data scientists, ML engineers, and business stakeholders to build and maintain robust MLOps pipelines, enabling rapid experimentation and reliable production implementation of AI models, including LLMs and real-time analytics systems. To be successful as Cloud Engineer you should have experience with: Cloud sourcing, networks, VMs, performance, scaling, availability, storage, security, access management Deep expertise in one or more cloud platforms: AWS, Azure, GCP Strong experience in containerization and orchestration (Docker, Kubernetes, Helm) Familiarity with CI/CD tools: GitHub Actions, Jenkins, Azure DevOps, ArgoCD, etc. Proficiency in scripting languages (Python, Bash, PowerShell) Knowledge of MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML Strong understanding of DevOps principles applied to ML workflows. Key Responsibilities may include: · Design and implement scalable, cost-optimized, and secure infrastructure for AI-driven platforms. · Implement infrastructure as code using tools like Terraform, ARM, or Cloud Formation. · Automate infrastructure provisioning, CI/CD pipelines, and model deployment workflows. · Ensure version control, repeatability, and compliance across all infrastructure components. · Set up monitoring, logging, and alerting frameworks using tools like Prometheus, Grafana, ELK, or Azure Monitor. · Optimize performance and resource utilization of AI workloads including GPU-based training/inference Experience with Snowflake, Databricks for collaborative ML development and scalable data processing. Understanding model interpretability, responsible AI, and governance. Contributions to open-source MLOps tools or communities. Strong leadership, communication, and cross-functional collaboration skills. Knowledge of data privacy, model governance, and regulatory compliance in AI systems. Exposure to LangChain, Vector DBs (e. g. , FAISS, Pinecone), and retrieval-augmented generation (RAG) pipelines. Show more Show less

Manage total pricing procedure and ensure timely response to market conditions. Support developing the pricing strategy formulation to remain competitive and enhance profitability. Analyze competition and industry trend. Develop pricing strategy across various product lines to position the products based on value and competitive situation.  Develop Methodology for calculating List Price, Price Floor, Price ceiling for various product lines within various market segments in relation to the value. Maintain corporate price list and periodically update appropriately  Develop tools for estimating cost for quotes for new products.  Transition the organization from cost plus pricing model to value pricing model  Develop value pricing model and implement it for all new products.  Define approval standards and processes  Perform financial evaluation to assess pricing action effectiveness  Lead the Price increase process/change management process for the organization. Work with sales, management, and product managers to implement the Price changes into the market and to product  Business cases for new pricing proposals  Bespoke pricing proposals with authority matrix and compliance  Conduct training on pricing to sales teams  Propose new models and product features to improve gross margin and increase revenue  Conduct field research including competition analysis, industry analysis , trend tracking and develop Insights based on inference  Develop a methodology to identify margin leakages and recommend approaches of improvement  Perform partnering with buyers, product managers and sales department to ensure integrated profit maximizing approach to market  Analyse financial impact of price approach in view of overall history as well as profitability of customer Performance Indicators  Top line revenue growth  Improved Margins  Average revenue per contract  Customer acquisition cost  Lifetime value 8 yrs overall experience with at least 3 years in a similar role Graduation in a relevant stream In depth knowledge of pricing strategies, processes, initiatives and creating pricing process documentation. Experience in SaaS pricing models and Value based pricing Proficiency in Data Mining Good understanding of the business model Numerical data Analytical mind with a strategic ability Strong attention to detail. Understanding of Financial Statements Excellent communication, negotiation and stakeholder management skills Skills:- Pricing Strategy, Pricing management and Revenue growth Show more Show less

Description We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place. We’re looking for an experienced Data Scientist who will help us build marketing attribution, causal inference, and uplift models to improve the effectiveness and efficiency of our marketing efforts. This person will also design experiments and help us drive consistent approach to experimentation and campaign measurement to support a range of marketing, customer engagement, and digital use cases. This Lead Data Scientist brings significant experience in designing, developing, and delivering statistical models and AI/ML algorithms for marketing and digital optimization use cases on large-scale data sets in a cloud environment. They show rigor in how they prototype, test, and evaluate algorithm performance both in the testing phase of algorithm development and in managing production algorithms. They demonstrate advanced knowledge of statistical and machine learning techniques along with ensuring the ethical use of data in the algorithm design process. At Salesforce, Trust is our number one value and we expect all applications of statistical and machine learning models to adhere to our values and policies to ensure we balance business needs with responsible uses of technology. Responsibilities As part of the Marketing Effectiveness Data Science team within the Salesforce Marketing Data Science organization, develop statistical and machine learning models to improve marketing effectiveness - e.g., marketing attribution models, causal inference models, uplift models, etc. Develop optimization and simulation algorithms to provide marketing investment and allocation recommendations to improve ROI by optimizing spend across marketing channels. Own the full lifecycle of model development from ideation and data exploration, algorithm design and testing, algorithm development and deployment, to algorithm monitoring and tuning in production. Design experiments to support marketing, customer experience, and digital campaigns and develop statistically sound models to measure impact. Collaborate with other data scientists to develop and operationalize consistent approaches to experimentation and campaign measurement. Be a master in cross-functional collaboration by developing deep relationships with key partners across the company and coordinating with working teams. Constantly learn, have a clear pulse on innovation across the enterprise SaaS, AdTech, paid media, data science, customer data, and analytics communities. Required Skills Master’s or Ph.D. in a quantitative field such as statistics, economics, industrial engineering and operations research, applied math, or other relevant quantitative field. 8+ years of experience designing models for marketing optimization such as multi-channel attribution models, customer lifetime value models, propensity models, uplift models, etc. using statistical and machine learning techniques. 8+ years of experience using advanced statistical techniques for experiment design (A/B and multi-cell testing) and causal inference methods for understanding business impact. Must have multiple, robust examples of using these techniques to measure effectiveness of marketing efforts and to solve business problems on large-scale data sets. 8+ years of experience with one or more programming languages such as Python, R, PySpark, Java. Expert-level knowledge of SQL with strong data exploration and manipulation skills. Experience using cloud platforms such as GCP and AWS for model development and operationalization is preferred. Must have superb quantitative reasoning and interpretation skills with strong ability to provide analysis-driven business insight and recommendations. Excellent written and verbal communication skills; ability to work well with peers and leaders across data science, marketing, and engineering organizations. Creative problem-solver who simplifies problems to their core elements. B2B customer data experience a big plus. Advanced Salesforce product knowledge is also a plus. Show more Show less

At Livello we building machine-learning-based demand forecasting tools as well as computer-vision-based multi-camera product recognition solutions that detects people and products to track the inserted/removed items on shelves based on the hand movement of users. We are building models to determine real-time inventory levels, user behaviour as well as predicting how much of each product needs to be reordered so that the right products are delivered to the right locations at the right time, to fulfil customer demand. Responsibilities Lead the CV and DS Team Work in the area of Computer Vision and Machine Learning, with focus on product (primarily food) and people recognition (position, movement, age, gender, DSGVO compliant). Your work will include formulation and development of a Machine Learning models to solve the underlying problem. You help build our smart supply chain system, keep up to date with the latest algorithmic improvements in forecasting and predictive areas, challenge the status quo Statistical data modelling and machine learning research. Conceptualize, implement and evaluate algorithmic solutions for supply forecasting, inventory optimization, predicting sales, and automating business processes Conduct applied research to model complex dependencies, statistical inference and predictive modelling Technological conception, design and implementation of new features Quality assurance of the software through planning, creation and execution of tests Work with a cross-functional team to define, build, test, and deploy applications Requirements Master/PHD in Mathematics, Statistics, Engineering, Econometrics, Computer Science or any related fields. 3-4 years of experience with computer vision and data science. Relevant Data Science experience, deep technical background in applied data science (machine learning algorithms, statistical analysis, predictive modelling, forecasting, Bayesian methods, optimization techniques). Experience building production-quality and well-engineered Computer Vision and Data Science products. Experience in image processing, algorithms and neural networks. Knowledge of the tools, libraries and cloud services for Data Science. Ideally Google Cloud Platform Solid Python engineering skills and experience with Python, Tensorflow, Docker Cooperative and independent work, analytical mindset, and willingness to take responsibility Fluency in English, both written and spoken. Skills:- Natural Language Processing (NLP), Computer Vision, TensorFlow, Docker, Forecasting, Predictive modelling, Image Processing, Algorithms and Machine Learning (ML) Show more Show less

Job Description Oracle Cloud Infrastructure (OCI) is a strategic growth area for Oracle. It is a comprehensive cloud service offering in the enterprise software industry, spanning Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). OCI is currently building a future-ready Gen2 cloud Data Science service platform. At the core of this platform, lies Cloud AI Cloud Service. What OCI AI Cloud Services are: A set of services on the public cloud, that are powered by ML and AI to meet the Enterprise modernization needs, and that work out of the box. These services and models can be easily specialized for specific customers/domains by demonstrating existing OCI services. Key Points: Enables customers to add AI capabilities to their Apps and Workflows easily via APIs or Containers, Useable without needing to build AI expertise in-house and Covers key gaps – Decision Support, NLP, for Public Clouds and Enterprise in NLU, NLP, Vision and Conversational AI. You’re Opportunity: As we innovate to provide a single collaborative ML environment for data-science professionals, we will be extremely happy to have you join us and share the very future of our Machine Learning platform - by building an AI Cloud service. We are addressing exciting challenges at the intersection of artificial intelligence and innovative cloud infrastructure. We are building cloud services in Computer vision for Image/Video and Document Analysis, Decision Support (Anomaly Detection, Time series forecasting, Fraud detection, Content moderation, Risk prevention, predictive analytics), Natural Language Processing (NLP), and, Speech that works out of the box for enterprises. Our product vision includes the ability for enterprises to be able to customize the services for their business and train them to specialize in their data by creating micro models that enhance the global AI models. What You’ll Do Develop scalable infrastructure, including microservices and a backend, that automates training, deployment, and optimization of ML model inference. Building a core of Artificial Intelligence and AI services such as Vision, Speech, Language, Decision, and others. Brainstorm and design various POCs using AI Perpetual AI Services for new or existing enterprise problems. Collaborate with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively communicating your needs, understanding theirs, and addressing external and internal shareholder product challenges. Lead research and development efforts to explore new tools, frameworks, and methodologies to improve backend development processes. Experiment with ML models in Python/C++ using machine learning libraries (Pytorch, ONNX, TensorRT, Triton, TensorFlow, Jax), etc. Leverage Cloud technology – Oracle Cloud (OCI), AWS, GCP, Azure, or similar technology. Qualifications Master’s degree or equivalent experience (preferred) in computer science, Statistics or Mathematics, artificial intelligence, machine learning, Computer vision, operations research, or related technical field. 3+ years for PhD or equivalent experience, 5+ years for Masters, or demonstrated ability designing, implementing, and deploying machine learning models in production environments. Practical experience in design, implementation, and production deployment of distributed systems using microservices architecture and APIs using common frameworks like Spring Boot (Java), etc. Practical experience working in a cloud environment: Oracle Cloud (OCI), AWS, GCP, Azure, and containerization (Docker, Kubernetes). Working knowledge of current techniques, approaches, and inference optimization strategies in machine learning models. Experience with performance tuning, scalability, and load balancing techniques. Expert in at least one high-level language such as Java/C++ (Java preferred). Expert in at least one scripting language such as Python, Javascript, and Shell . Deep understanding of data structures, and algorithms, and excellent problem-solving skills. Experience or willingness to learn and work in Agile and iterative development and DevOps processes. Strong drive to learn and master new technologies and techniques. You enjoy a fast-paced work environment. Additional Preferred Qualifications Experience with Cloud Native Frameworks tools and products is a plus Experience in Computer vision tasks like Image Classification, Object Detection, Segmentation, Text detection & recognition, Information extraction from documents, etc. Having an impressive set of GitHub projects or contributions to open-source technologies is a plus Hands-on experience with horizontally scalable data stores such as Hadoop and other NoSQL technologies like Cassandra is a plus. Our vision is to provide an immersive AI experience on Oracle Cloud. Aggressive as it might sound, our growth journey is fueled by highly energetic, technology-savvy engineers like YOU who are looking to grow with us to meet the demands of building a powerful next-generation platform. Are you ready to do something big? Career Level - IC3 About Us As a world leader in cloud solutions, Oracle uses tomorrow’s technology to tackle today’s challenges. We’ve partnered with industry-leaders in almost every sector—and continue to thrive after 40+ years of change by operating with integrity. We know that true innovation starts when everyone is empowered to contribute. That’s why we’re committed to growing an inclusive workforce that promotes opportunities for all. Oracle careers open the door to global opportunities where work-life balance flourishes. We offer competitive benefits based on parity and consistency and support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing accommodation-request_mb@oracle.com or by calling +1 888 404 2494 in the United States. Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law. Show more Show less

Job Description Oracle Cloud Infrastructure (OCI) is a strategic growth area for Oracle. It is a comprehensive cloud service offering in the enterprise software industry, spanning Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). OCI is currently building a future-ready Gen2 cloud Data Science service platform. At the core of this platform, lies Cloud AI Cloud Service. What OCI AI Cloud Services are: A set of services on the public cloud, that are powered by ML and AI to meet the Enterprise modernization needs, and that work out of the box. These services and models can be easily specialized for specific customers/domains by demonstrating existing OCI services. Key Points: Enables customers to add AI capabilities to their Apps and Workflows easily via APIs or Containers, Useable without needing to build AI expertise in-house and Covers key gaps – Decision Support, NLP, for Public Clouds and Enterprise in NLU, NLP, Vision and Conversational AI. You’re Opportunity: As we innovate to provide a single collaborative ML environment for data-science professionals, we will be extremely happy to have you join us and share the very future of our Machine Learning platform - by building an AI Cloud service. We are addressing exciting challenges at the intersection of artificial intelligence and innovative cloud infrastructure. We are building cloud services in Computer vision for Image/Video and Document Analysis, Decision Support (Anomaly Detection, Time series forecasting, Fraud detection, Content moderation, Risk prevention, predictive analytics), Natural Language Processing (NLP), and, Speech that works out of the box for enterprises. Our product vision includes the ability for enterprises to be able to customize the services for their business and train them to specialize in their data by creating micro models that enhance the global AI models. What You’ll Do Develop scalable infrastructure, including microservices and a backend, that automates training, deployment, and optimization of ML model inference. Building a core of Artificial Intelligence and AI services such as Vision, Speech, Language, Decision, and others. Brainstorm and design various POCs using AI Perpetual AI Services for new or existing enterprise problems. Collaborate with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively communicating your needs, understanding theirs, and addressing external and internal shareholder product challenges. Lead research and development efforts to explore new tools, frameworks, and methodologies to improve backend development processes. Experiment with ML models in Python/C++ using machine learning libraries (Pytorch, ONNX, TensorRT, Triton, TensorFlow, Jax), etc. Leverage Cloud technology – Oracle Cloud (OCI), AWS, GCP, Azure, or similar technology. Qualifications Master’s degree or equivalent experience (preferred) in computer science, Statistics or Mathematics, artificial intelligence, machine learning, Computer vision, operations research, or related technical field. 3+ years for PhD or equivalent experience, 5+ years for Masters, or demonstrated ability designing, implementing, and deploying machine learning models in production environments. Practical experience in design, implementation, and production deployment of distributed systems using microservices architecture and APIs using common frameworks like Spring Boot (Java), etc. Practical experience working in a cloud environment: Oracle Cloud (OCI), AWS, GCP, Azure, and containerization (Docker, Kubernetes). Working knowledge of current techniques, approaches, and inference optimization strategies in machine learning models. Experience with performance tuning, scalability, and load balancing techniques. Expert in at least one high-level language such as Java/C++ (Java preferred). Expert in at least one scripting language such as Python, Javascript, and Shell . Deep understanding of data structures, and algorithms, and excellent problem-solving skills. Experience or willingness to learn and work in Agile and iterative development and DevOps processes. Strong drive to learn and master new technologies and techniques. You enjoy a fast-paced work environment. Additional Preferred Qualifications Experience with Cloud Native Frameworks tools and products is a plus Experience in Computer vision tasks like Image Classification, Object Detection, Segmentation, Text detection & recognition, Information extraction from documents, etc. Having an impressive set of GitHub projects or contributions to open-source technologies is a plus Hands-on experience with horizontally scalable data stores such as Hadoop and other NoSQL technologies like Cassandra is a plus. Our vision is to provide an immersive AI experience on Oracle Cloud. Aggressive as it might sound, our growth journey is fueled by highly energetic, technology-savvy engineers like YOU who are looking to grow with us to meet the demands of building a powerful next-generation platform. Are you ready to do something big? Career Level - IC3 About Us As a world leader in cloud solutions, Oracle uses tomorrow’s technology to tackle today’s challenges. We’ve partnered with industry-leaders in almost every sector—and continue to thrive after 40+ years of change by operating with integrity. We know that true innovation starts when everyone is empowered to contribute. That’s why we’re committed to growing an inclusive workforce that promotes opportunities for all. Oracle careers open the door to global opportunities where work-life balance flourishes. We offer competitive benefits based on parity and consistency and support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing accommodation-request_mb@oracle.com or by calling +1 888 404 2494 in the United States. Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law. Show more Show less

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Meet Our Team Sr. Data Scientist – Job description The Data & Analytics organization is at the forefront of developing and maintaining frameworks, tools, and data products vital to WBD, including flagship streaming product Max and non-streaming products such as Films Group, Sports, News and overall WBD eco-system. Our mission is to foster unified analytics and drive data-driven use cases by leveraging a robust multi-tenant platform and semantic layer. We are committed to delivering innovative solutions that empower teams across the company to catalyze subscriber growth, amplify engagement, and execute timely, informed decisions, ensuring our continued success in an ever-evolving digital landscape. Roles & Responsibilities The role will focus on building out machine learning solutions for WBD’s Data and Analytics organization. Primary focus will be on unlocking machine learning opportunities and building foundational machine learning training and inference pipelines at scale. You have a deep understanding of different types of data, metrics and KPIs. You will lead by example and define the best practices, will set high standards for the entire team and for the rest of the organization. You have a successful track record for ambitious projects across cross-functional teams. You are passionate and results oriented. You strive for technical excellence and are very hands-on. Your co-workers love working with you. You have built respect in your career through concrete accomplishments. Build cutting-edge capabilities utilizing machine learning and data science (e.g., large language models, computer vision models, advanced ad & content targeting, etc.) Lead data science and model development techniques for the team. Leverage industry best practices and tools to continually improve teams' ability to build machine learning models. What To Bring BA/BS in statistics, mathematics, economics, industrial engineering, or other quantitative discipline is required. Masters/PhD is a plus 4+ years of experience building data science/statistical models (Multivariate regression, Time Series Model, XGBoost, Causal inference etc.) Strong understanding of modern ML approaches (GBDT, CNN, LSTM, GRU, HRNN, transformers, siamese neural networks, variational auto-encoders, ...). Experience with Deep Learning, NLP, LLMs, Reinforcement Learning, Causal Inference. Good knowledge of ML tools and frameworks (TensorFlow, Keras, pyTorch, scikit-learn, Spark,...). Proficiency in programming languages such as Python or R. Familiarity with real-world ML systems (configuration, data collection, data verification, feature extraction, resource and process management, analytics, training, serving, validation, experimentation, monitoring). Good understanding of operating machine learning solutions at scale, covering the end-to-end ML workflow. Strong interpersonal skills with the ability to motivate, collaborate and influence Ability to deliver on multiple projects and meet tight deadlines Ability to effectively influence and communicate cross-functionally with all levels How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request. Show more Show less

Job Description Oracle Cloud Infrastructure (OCI) is a strategic growth area for Oracle. It is a comprehensive cloud service offering in the enterprise software industry, spanning Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). OCI is currently building a future-ready Gen2 cloud Data Science service platform. At the core of this platform, lies Cloud AI Cloud Service. What OCI AI Cloud Services are: A set of services on the public cloud, that are powered by ML and AI to meet the Enterprise modernization needs, and that work out of the box. These services and models can be easily specialized for specific customers/domains by demonstrating existing OCI services. Key Points: Enables customers to add AI capabilities to their Apps and Workflows easily via APIs or Containers, Useable without needing to build AI expertise in-house and Covers key gaps – Decision Support, NLP, for Public Clouds and Enterprise in NLU, NLP, Vision and Conversational AI. You’re Opportunity: As we innovate to provide a single collaborative ML environment for data-science professionals, we will be extremely happy to have you join us and share the very future of our Machine Learning platform - by building an AI Cloud service. We are addressing exciting challenges at the intersection of artificial intelligence and innovative cloud infrastructure. We are building cloud services in Computer vision for Image/Video and Document Analysis, Decision Support (Anomaly Detection, Time series forecasting, Fraud detection, Content moderation, Risk prevention, predictive analytics), Natural Language Processing (NLP), and, Speech that works out of the box for enterprises. Our product vision includes the ability for enterprises to be able to customize the services for their business and train them to specialize in their data by creating micro models that enhance the global AI models. What You’ll Do Develop scalable infrastructure, including microservices and a backend, that automates training, deployment, and optimization of ML model inference. Building a core of Artificial Intelligence and AI services such as Vision, Speech, Language, Decision, and others. Brainstorm and design various POCs using AI Perpetual AI Services for new or existing enterprise problems. Collaborate with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively communicating your needs, understanding theirs, and addressing external and internal shareholder product challenges. Lead research and development efforts to explore new tools, frameworks, and methodologies to improve backend development processes. Experiment with ML models in Python/C++ using machine learning libraries (Pytorch, ONNX, TensorRT, Triton, TensorFlow, Jax), etc. Leverage Cloud technology – Oracle Cloud (OCI), AWS, GCP, Azure, or similar technology. Qualifications Master’s degree or equivalent experience (preferred) in computer science, Statistics or Mathematics, artificial intelligence, machine learning, Computer vision, operations research, or related technical field. 3+ years for PhD or equivalent experience, 5+ years for Masters, or demonstrated ability designing, implementing, and deploying machine learning models in production environments. Practical experience in design, implementation, and production deployment of distributed systems using microservices architecture and APIs using common frameworks like Spring Boot (Java), etc. Practical experience working in a cloud environment: Oracle Cloud (OCI), AWS, GCP, Azure, and containerization (Docker, Kubernetes). Working knowledge of current techniques, approaches, and inference optimization strategies in machine learning models. Experience with performance tuning, scalability, and load balancing techniques. Expert in at least one high-level language such as Java/C++ (Java preferred). Expert in at least one scripting language such as Python, Javascript, and Shell . Deep understanding of data structures, and algorithms, and excellent problem-solving skills. Experience or willingness to learn and work in Agile and iterative development and DevOps processes. Strong drive to learn and master new technologies and techniques. You enjoy a fast-paced work environment. Additional Preferred Qualifications Experience with Cloud Native Frameworks tools and products is a plus Experience in Computer vision tasks like Image Classification, Object Detection, Segmentation, Text detection & recognition, Information extraction from documents, etc. Having an impressive set of GitHub projects or contributions to open-source technologies is a plus Hands-on experience with horizontally scalable data stores such as Hadoop and other NoSQL technologies like Cassandra is a plus. Our vision is to provide an immersive AI experience on Oracle Cloud. Aggressive as it might sound, our growth journey is fueled by highly energetic, technology-savvy engineers like YOU who are looking to grow with us to meet the demands of building a powerful next-generation platform. Are you ready to do something big? Career Level - IC3 About Us As a world leader in cloud solutions, Oracle uses tomorrow’s technology to tackle today’s challenges. We’ve partnered with industry-leaders in almost every sector—and continue to thrive after 40+ years of change by operating with integrity. We know that true innovation starts when everyone is empowered to contribute. That’s why we’re committed to growing an inclusive workforce that promotes opportunities for all. Oracle careers open the door to global opportunities where work-life balance flourishes. We offer competitive benefits based on parity and consistency and support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing accommodation-request_mb@oracle.com or by calling +1 888 404 2494 in the United States. Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law. Show more Show less

Role: Applied AI Engineer (Vision/GenAI) Function: Applied AI Engineer Location: Gurgaon Type: Full-time Compensation: 40 - 60 LPA + ESOPs About the Company: An early-stage, US-based venture-backed technology company focused on creating innovative platforms for building meaningful relationships. They aim to transform how people connect by harnessing artificial intelligence, fostering community engagement, and delivering tailored content. Rather than developing another conventional social app, they’re crafting a unique experience that resonates deeply with users, making them feel truly understood. Central to our platform is a dynamic, machine-learning-powered recommendation system, drawing inspiration from the personalised discovery engines of leading music and video platforms. With strong financial backing from top-tier venture capital firms in India and the United States, they are well-positioned to advance our mission with innovation and impact. Company Philosophy: They believe: Great data + Good models = Great recommendations Good data + Great models = Average recommendations That’s why they’re investing in data infrastructure from our inception and foundation. Position Overview: As an Applied AI Engineer, you'll lead the deployment of advanced vision-language models to power a personalised, photorealistic user experience. Your work will focus on fine-tuning and integrating models like Stable Diffusion, LoRA, and CLIP into real-time pipelines, optimising them for user delight, performance, accuracy, and eventually costs. You will collaborate closely with product and design teams to bring generative AI capabilities to deliver a novel dating experience. Role & Responsibilities: Build and deploy cutting-edge vision-language pipelines (e.g., Stable Diffusion, LoRA, CLIP, BLIP) for personalized and authentic user profile visuals Fine-tune LoRA models to reflect a user's best version while maintaining identity integrity Design scalable APIs for image generation, editing, and personalization Work with UX/design to integrate image-generation flows that feel intuitive and delightful Optimize models for mobile performance, fast inference, and cost efficiency Collaborate closely with product, backend, and ML researchers to productionize ideas Ideal Profile: We are looking for a hands-on applied AI/ML engineer with expertise in generative vision models like Stable Diffusion, and some track record of building real-time, personalised generative AI experiences. Experience with computer vision, generative models, or deep learning Experience working with Stable Diffusion, LoRA training, and prompt engineering Exposure to different vision-language architectures like Flux, CLIP, BLIP etc Proficient in PyTorch or equivalent ML frameworks Strong understanding of image pipelines, dataset curation, and captioning Experience deploying ML models on cloud-based services ( at minimum Replicate, Hugging Face Spaces and preferably on GPUs) Comfortable writing production-ready Python, working with versioned models and real-time inference stacks Passionate about building beautiful, human-centred AI experiences Nice to have: Prior experience with personalization, avatars, or face-preserving generative models Contributed to open-source vision models or fine-tuning libraries Experience in a startup or fast-paced product-focused team What we offer: Join a founding team where your work is core to product experience Shape the future of how humans connect in the AI era Significant ESOPs and wealth creation + competitive cash compensation Show more Show less

Job Description Expertise in handling large scale structured and unstructured data. Efficiently handled large-scale generative AI datasets and outputs. Familiarity in the use of Docker tools, pipenv/conda/poetry env Comfort level in following Python project management best practices (use of setup.py, logging, pytests, relative module imports,sphinx docs,etc.,) Familiarity in use of Github (clone, fetch, pull/push,raising issues and PR, etc.,) High familiarity in the use of DL theory/practices in NLP applications Comfort level to code in Huggingface, LangChain, Chainlit, Tensorflow and/or Pytorch, Scikit-learn, Numpy and Pandas Comfort level to use two/more of open source NLP modules like SpaCy, TorchText, fastai.text, farm-haystack, and others Knowledge in fundamental text data processing (like use of regex, token/word analysis, spelling correction/noise reduction in text, segmenting noisy unfamiliar sentences/phrases at right places, deriving insights from clustering, etc.,) Have implemented in real-world BERT/or other transformer fine-tuned models (Seq classification, NER or QA) from data preparation, model creation and inference till deployment Use of GCP services like BigQuery, Cloud function, Cloud run, Cloud Build, VertexAI, Good working knowledge on other open source packages to benchmark and derive summary Experience in using GPU/CPU of cloud and on-prem infrastructures Responsibilities Design NLP/LLM/GenAI applications/products by following robust coding practices, Explore SoTA models/techniques so that they can be applied for automotive industry usecases Conduct ML experiments to train/infer models; if need be, build models that abide by memory & latency restrictions, Deploy REST APIs or a minimalistic UI for NLP applications using Docker and Kubernetes tools Showcase NLP/LLM/GenAI applications in the best way possible to users through web frameworks (Dash, Plotly, Streamlit, etc.,) Converge multibots into super apps using LLMs with multimodalities Develop agentic workflow using Autogen, Agentbuilder, langgraph Build modular AI/ML products that could be consumed at scale Qualifications Education : Bachelor’s in Engineering or Master’s Degree in Computer Science, Engineering, Maths or Science Performed any modern NLP/LLM courses/open competitions is also welcomed. Show more Show less

Graviton is a privately funded quantitative trading firm striving for excellence in financial markets research. We are seeking an HPC Engineer for our team in Gurgaon. Graviton trades across a multitude of asset classes and trading venues using a gamut of concepts and techniques ranging from time series analysis, filtering, classification, stochastic models, and pattern recognition to statistical inference analysing terabytes of data to come up with ideas to identify pricing anomalies in financial markets. Responsibilities Experience in High-Performance Computing with extensive practical hands-on experience in deploying High-Performance Clusters Have experience with cluster management Tools Worked on Parallel Filesystem Environments - Optional Exposure to multiprocessor and multithreading concepts Experienced with Operating Systems: Linux. Testing, User Support and Troubleshooting, RTA of issues. Qualifications The ideal candidate will have 2-3 years of experience with Degree in EE/CS/CSE. Bachelors graduates will also be considered with exceptional background and prior experience in HPC field. Proficient in programming skills in Python/Bash Good understanding and exposure to the Linux operating system at the user level. Experience with large-scale distributed HPC systems Understanding of large-scale batch processing systems(PBS Pro/Torque/Slurm); approaches to efficient scheduling; Preferred HPC system monitoring and automation tools. Benefits: Our open and collaborative work culture gives you the freedom to innovate and experiment. Our cubicle free offices, non-hierarchical work culture and insistence to hire the very best creates a melting pot for great ideas and technological innovations. Everyone on the team is approachable, there is nothing better than working with friends! Our perks have you covered. Competitive compensation Annual international team outing Fully covered commuting expenses Best-in-class health insurance Delightful catered breakfasts and lunches A well-stocked kitchen 4 week annual leaves along with market holidays Gym and sports club memberships Regular social events and clubs After work parties Show more Show less

Overview: Data Science Team works in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. Specific scope of this role is to develop ML solution in support of ML/AI projects using big analytics toolsets in a CI/CD environment. Analytics toolsets may include DS tools/Spark/Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. This role will also help automate the end-to-end cycle with Azure Pipelines. You will be part of a collaborative interdisciplinary team around data, where you will be responsible of our continuous delivery of statistical/ML models. You will work closely with process owners, product owners and final business users. This will provide you the correct visibility and understanding of criticality of your developments. Responsibilities: Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope Active contributor to code & development in projects and services Partner with data engineers to ensure data access for discovery and proper data is prepared for model consumption. Partner with ML engineers working on industrialization. Communicate with business stakeholders in the process of service design, training and knowledge transfer. Support large-scale experimentation and build data-driven models. Refine requirements into modelling problems. Influence product teams through data-based recommendations. Research in state-of-the-art methodologies. Create documentation for learnings and knowledge transfer. Create reusable packages or libraries. Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards Leverage big data technologies to help process data and build scaled data pipelines (batch to real time) Implement end-to-end ML lifecycle with Azure Databricks and Azure Pipelines Automate ML models deployments Qualifications: BE/B.Tech in Computer Science, Maths, technical fields. Overall 2-4 years of experience working as a Data Scientist. 2+ years’ experience building solutions in the commercial or in the supply chain space. 2+ years working in a team to deliver production level analytic solutions. Fluent in git (version control). Understanding of Jenkins, Docker are a plus. Fluent in SQL syntaxis. 2+ years’ experience in Statistical/ML techniques to solve supervised (regression, classification) and unsupervised problems. 2+ years’ experience in developing business problem related statistical/ML modeling with industry tools with primary focus on Python or Pyspark development. Data Science – Hands on experience and strong knowledge of building machine learning models – supervised and unsupervised models. Knowledge of Time series/Demand Forecast models is a plus Programming Skills – Hands-on experience in statistical programming languages like Python, Pyspark and database query languages like SQL Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators Cloud (Azure) – Experience in Databricks and ADF is desirable Familiarity with Spark, Hive, Pig is an added advantage Business storytelling and communicating data insights in business consumable format. Fluent in one Visualization tool. Strong communications and organizational skills with the ability to deal with ambiguity while juggling multiple priorities Experience with Agile methodology for team work and analytics ‘product’ creation. Experience in Reinforcement Learning is a plus. Experience in Simulation and Optimization problems in any space is a plus. Experience with Bayesian methods is a plus. Experience with Causal inference is a plus. Experience with NLP is a plus. Experience with Responsible AI is a plus. Experience with distributed machine learning is a plus Experience in DevOps, hands-on experience with one or more cloud service providers AWS, GCP, Azure(preferred) Model deployment experience is a plus Experience with version control systems like GitHub and CI/CD tools Experience in Exploratory data Analysis Knowledge of ML Ops / DevOps and deploying ML models is preferred Experience using MLFlow, Kubeflow etc. will be preferred Experience executing and contributing to ML OPS automation infrastructure is good to have Exceptional analytical and problem-solving skills Stakeholder engagement-BU, Vendors. Experience building statistical models in the Retail or Supply chain space is a plus

Technical Expertise : (minimum 2 year relevant experience) ● Solid understanding of Generative AI models and Natural Language Processing (NLP) techniques, including Retrieval-Augmented Generation (RAG) systems, text generation, and embedding models. ● Exposure to Agentic AI concepts, multi-agent systems, and agent development using open-source frameworks like LangGraph and LangChain. ● Hands-on experience with modality-specific encoder models (text, image, audio) for multi-modal AI applications. ● Proficient in model fine-tuning, prompt engineering, using both open-source and proprietary LLMs. ● Experience with model quantization, optimization, and conversion techniques (FP32 to INT8, ONNX, TorchScript) for efficient deployment, including edge devices. ● Deep understanding of inference pipelines, batch processing, and real-time AI deployment on both CPU and GPU. ● Strong MLOps knowledge with experience in version control, reproducible pipelines, continuous training, and model monitoring using tools like MLflow, DVC, and Kubeflow. ● Practical experience with scikit-learn, TensorFlow, and PyTorch for experimentation and production-ready AI solutions. ● Familiarity with data preprocessing, standardization, and knowledge graphs (nice to have). ● Strong analytical mindset with a passion for building robust, scalable AI solutions. ● Skilled in Python, writing clean, modular, and efficient code. ● Proficient in RESTful API development using Flask, FastAPI, etc., with integrated AI/ML inference logic. ● Experience with MySQL, MongoDB, and vector databases like FAISS, Pinecone, or Weaviate for semantic search. ● Exposure to Neo4j and graph databases for relationship-driven insights. ● Hands-on with Docker and containerization to build scalable, reproducible, and portable AI services. ● Up-to-date with the latest in GenAI, LLMs, Agentic AI, and deployment strategies. ● Strong communication and collaboration skills, able to contribute in cross-functional and fast-paced environments. Bonus Skills ● Experience with cloud deployments on AWS, GCP, or Azure, including model deployment and model inferencing. ● Working knowledge of Computer Vision and real-time analytics using OpenCV, YOLO, and similar Job Type: Full-time Pay: From ₹300,000.00 per year Schedule: Day shift Experience: AI Engineer: 1 year (Required) Work Location: In person Expected Start Date: 23/06/2025

We're not your average tech company! Rightcrowd is a global leader in keeping people safe and organizations secure. We build smart solutions that manage who's on-site, what access they have, and ensure everything is compliant. Think big names – Fortune 50 and ASX 10 companies rely on us to tackle their toughest security challenges. We're a passionate, global team with offices in places like Australia, the USA, Belgium, India, and the Philippines, and we're on a mission to make the world a safer place, one clever line of code at a time. What We Offer Competitive salary and benefits. A collaborative, respectful, and high-accountability team culture. Opportunities for growth within a global finance team. Flexibility in a remote-friendly and dynamic work environment. Key Responsibilities: 1. Agentic AI Development & Code Generation: Design, implement, and lead the development of an advanced agentic AI system that can interpret user stories and autonomously generate production-ready code Research and implement state-of-the-art techniques in LLM prompting, fine-tuning, and orchestration to achieve optimal code generation results Architect robust evaluation systems to test, validate, and improve AI-generated code Seamlessly integrate AI-generated code into existing CI/CD pipelines Collaborate with product and engineering teams to refine inputs and ensure alignment with development standards 2. AI Recommendation Engine Architecture: Architect a high-performance, scalable recommendation engine for the RightCrowd SmartAccess platform Design and implement AI-driven feature extraction pipelines Develop hybrid recommendation algorithms leveraging both collaborative filtering and content- based approaches Engineer systems for real-time inference and continuous model improvement Ensure the architecture integrates seamlessly with existing product infrastructure 3. Natural Language Reporting System Development: Lead the end-to-end development of an AI-powered reporting system that translates natural language queries to SQL Engineer robust NLP components to accurately understand and parse user requests Build a reliable translation layer between natural language and database queries Implement data retrieval, processing, and presentation mechanisms Design systems for generating insights and visualizations from retrieved data• Ensure appropriate data security and access controls 4. Technical Leadership & Innovation: Provide architectural guidance across AI initiatives within the organization Design scalable, maintainable AI systems with consideration for cloud infrastructure and MLOps best practices Stay at the forefront of advancements in LLMs, agentic AI, and code generation technologies Mentor junior engineers and foster a culture of AI innovation Collaborate effectively with cross-functional teams Required Qualifications & Skills: Master's or Ph.D. in Computer Science, AI, or related field (or equivalent practical experience) 5+ years of experience building production-level AI systems with significant focus on LLMs and generative AI Demonstrated expertise in Python and modern AI frameworks (PyTorch, TensorFlow, Hugging Face Transformers) Extensive experience with LLM orchestration frameworks (LangChain, LangGraph, or similar) Proven track record designing and implementing agentic AI systems Strong proficiency in prompt engineering, fine-tuning, and optimization of LLMs Expert-level SQL skills and experience with database systems Experience with cloud platforms (AWS, Azure, GCP) and their AI/ML services Solid understanding of software engineering principles and best practices Experience with MLOps and CI/CD pipelines for AI systems Preferred Qualifications: Experience developing systems that generate production-ready code Familiarity with retrieval-augmented generation (RAG) techniques Experience with vector databases (Pinecone, Weaviate, etc.) Knowledge of containerization technologies (Docker, Kubernetes) Experience with model optimization, quantization, and efficient inference Contributions to open-source AI projects or research publications Familiarity with physical security or identity access management domains Experience implementing AI systems with strong security and governance controls This position offers the opportunity to work at the forefront of AI engineering, developing systems that not only generate code but also function autonomously to deliver real business

Job Description: Join our pioneering team at BuzzBoard, a recognized first-mover in enterprise generative AI, as a Team Lead of Generative AI and LLM. We've already deployed production GenAI systems generating thousands of posts and content pieces monthly across our ecosystem. You'll lead the charge in scaling our mature AI infrastructure while architecting next-generation applications. As a key leader in our Product Team, you'll orchestrate collaboration between Data Engineering, Software Engineering, and AI Operations teams while expanding our proven generative AI innovations. Key Responsibilities: Strategic Leadership & Vision Lead and mentor a team of GenAI engineers and researchers within our mature AI ecosystem Scale our proven production AI systems generating thousands of content pieces monthly across multiple business verticals Define generative AI strategy and roadmap building upon our established first-mover advantage Drive adoption of multimodal AI systems incorporating vision, audio, and text capabilities Contribute and own the GenAI governance frameworks and best practices Advanced AI Development Architect and scale sophisticated generative AI systems building upon our established multi-LLM infrastructure (GPT-4o, Claude Sonnet, Gemini, O1) Optimize our proven tech stack including LangChain, CrewAI, LangGraph, and vector databases (Chroma) Implement advanced RAG, fine-tuning, and prompt engineering across our existing model inventory Lead development of next-generation agentic AI systems with tool use, reasoning capabilities, and autonomous decision-making Enhance our multi-agent orchestration platforms and complex workflow automation Technology Leadership Drive adoption of agentic AI frameworks including LangGraph, CrewAI, AutoGen, and Microsoft Semantic Kernel Lead implementation of multi-agent orchestration platforms and autonomous decision-making systems Oversee vector databases (Pinecone, Weaviate, Chroma) and semantic search systems Lead integration of AI observability and monitoring tools (LangSmith, Weights & Biases, MLflow) Champion AI development platforms and low-code/no-code solutions Enterprise Integration & Scaling Scale our mature AI infrastructure supporting thousands of monthly content generations across multiple business verticals Enhance our proven MLOps and LLMOps practices for continuous model deployment and performance monitoring Drive technical collaboration for seamless AI integration into established production systems Optimize edge AI capabilities and multi-environment deployment strategies Enhance our performance tracking framework including regression testing, edit ratio tracking, and analytics integration Skills and Qualifications: Core Technical Expertise Deep expertise in generative AI systems, large language models, and transformer architectures with proven production experience Expert proficiency in our established tech stack: LangChain, CrewAI, LangGraph, AutoGen, and multi-LLM orchestration Hands-on experience with our model ecosystem: OpenAI GPT, Anthropic, Google, and vector databases Extensive experience with agentic AI frameworks and autonomous workflow orchestration in production environments Hands-on with programming skills in Python with experience in FastAPI, Streamlit, and modern web frameworks Expert-level understanding of prompt engineering, fine-tuning techniques, and model optimization at scale AI Architecture & Operations Experience with vector databases, embedding models, and semantic search implementations Proficiency in containerization (Docker, Kubernetes) and cloud-native AI deployments Knowledge of AI model serving platforms (vLLM, TensorRT-LLM, Ollama) and inference optimization Understanding of AI safety, alignment, and responsible AI development practices Technical Leadership (Individual Contributor Focus) Experience providing technical guidance to engineering teams in fast-paced environments Experience with AI product development lifecycle and technical go-to-market strategies Strong technical communication and ability to explain AI concepts to technical and non-technical audiences Knowledge of AI regulation landscape and compliance requirements Modern AI Ecosystem Familiarity with AI agent frameworks (LangGraph, CrewAI, Microsoft Semantic Kernel) - REQUIRED Experience with compound AI systems and multi-step reasoning architectures - REQUIRED Experience with multimodal AI systems and computer vision integration Understanding of federated learning and privacy-preserving AI techniques Knowledge of AI model evaluation frameworks and benchmarking methodologies Advanced Qualifications: Agentic AI Mastery (Required) Extensive hands-on experience building and deploying agentic AI systems in production environments Deep understanding of tool-calling, function-calling, and API integration within agent workflows Proven track record with multi-agent collaboration patterns and complex reasoning chains Expertise in agent memory systems, context management, and state persistence across interactions Industry Integration Experience scaling production GenAI systems with proven track record of generating thousands of content pieces monthly Knowledge of multi-LLM orchestration and model switching strategies for optimal performance and cost efficiency Understanding of content generation workflows across social media, marketing, and business communications Familiarity with performance monitoring frameworks including regression testing and analytics dashboard integration Research & Innovation Experience with AI model interpretability and explainable AI techniques Knowledge of quantum-classical hybrid AI approaches and emerging paradigms Technical Excellence Advanced degree in Computer Science, AI, or related field (preferred) Experience building and scaling AI teams in fast-paced environments (preferred) Experience with AI ethics committees and responsible AI governance (preferred) Proven ability to drive digital transformation through AI adoption (preferred) Lead the future of GenAI innovation at BuzzBoard, where your expertise will build upon our established success in production generative AI systems. Join a first-mover organization that has already proven the enterprise value of GenAI at scale, generating thousands of content pieces monthly. Your role as Team Lead of Generative AI and LLM will position you to expand our proven AI ecosystem while defining the next generation of agentic AI solutions that drive measurable business impact. Powered by JazzHR 12dkkTUOj7 Show more Show less

Overview Overview: The GenAI Technical Solutions Architect develops and implements GEN AI achitecture strategies, best practices, and standards to enhance AI ML model deployment and monitoring efficiency. Develop architecture roadmap and strategy for GenAI Platforms and tech stacks. This role will focus on the technical development, deployment, Code reuse and optimization of GenAI solutions, ensuring alignment with business strategies and technological advancements. Responsibilities Responsibilities: Develop cutting-edge architectural strategies for Gen AI components and platforms, leveraging advanced techniques such as chunking, Retrieval-Augmented Generation (RAG), Ai agents, and embeddings. Balance build versus buy decisions, ensuring alignment with SaaS models and decision trees, particularly for the PepGenX platform. Emphasize low coupling and cohesive model development. Lead working sessions for Arch Alignment, pattern library development, GEN AI Tools Data Architect alignment, tag new components to reuse (components reuse strategy), patterns of the usecases, reuse components ( save efforts, time money). Lead the implementation of LLM operations, focusing on optimizing model performance, scalability, and efficiency. Design and implement LLM agentic processes to create autonomous AI systems capable of complex decision-making and task execution. Work closely with data scientists and AI professionals to identify and pilot innovative use cases that drive digital transformation. Assess the feasibility of these use cases, aligning them with business objectives, ROI and leveraging advanced AI techniques. Gather inputs from various stakeholders to align technical implementations with current and future requirements. Develop processes and products based on these inputs, incorporating state-of-the-art AI methodologies. Define AI architecture and select suitable technologies, with a focus on integrating RAG systems, embedding models, and advanced LLM frameworks. Decide on optimal deployment models, ensuring seamless integration with existing data management and analytics tools. Audit AI tools and practices, focusing on continuous improvement of LLM ops and agentic processes. Collaborate with security and risk leaders to mitigate risks such as data poisoning and model theft, ensuring ethical AI implementation. Stay updated on AI regulations and map them to best practices in AI architecture and pipeline planning. Develop expertise in ML and deep learning workflow architectures, with a focus on chunking strategies, embedding pipelines, and RAG system implementation. Apply advanced software engineering and DevOps principles, utilizing tools like Git, Kubernetes, and CI/CD for efficient LLM ops. Collaborate across teams to ensure AI platforms meet both business and technical requirements. Spearhead the exploration and application of cutting-edge Large Language Models (LLMs) and Generative AI, including multi-modal capabilities and agentic processes. Oversee MLOps, automating ML pipelines from training to deployment with a focus on RAG and embedding optimization. Engage in sophisticated model development from ideation to deployment, leveraging advanced chunking and RAG techniques. Effectively communicate complex analysis results to business partners and executives. Proactively reduce biases in model predictions, focusing on fair and inclusive AI systems through advanced debiasing techniques in embeddings and LLM training. Design efficient data pipelines to support large language model training and inference, with a focus on optimizing chunking strategies and embedding generation for RAG systems. Qualifications Experience: Proven track record in shipping products and developing state-of-the-art Gen AI product architecture. 10+ years of experience with a strong balance of business acumen and technical expertise in AI. 5+ years in building and releasing NLP/AI software, with specific experience in RAG , Agents systems and embedding models. Demonstrated experience in delivering Gen AI products, including Multi-modal LLMs, Foundation models, and agentic AI systems. Deep familiarity with cloud technologies, especially Azure, and experience deploying models for large-scale inference using advanced LLM ops techniques. Proficiency in PyTorch, TensorFlow, Kubernetes, Docker, LlamaIndex, LangChain, LLM, SLM, LAM, and cloud platforms, with a focus on implementing RAG and embedding pipelines. Excellent communication and interpersonal skills, with a strong design capability and ability to articulate complex AI concepts to diverse audiences. Hands-on experience with chunking strategies, RAG implementation, and optimizing embedding models for various AI applications. Qualifications: Bachelor’s or master’s degree in computer science, Data Science, or a related technical field. Demonstrated ability to translate complex technical concepts into actionable business strategies. Experience in data-driven decision-making processes. Strong communication skills, with the ability to collaborate effectively with both technical and non-technical stakeholders. Proven track record in managing and delivering AI/ML projects, with a focus on GenAI solutions, in large-scale enterprise environments. Show more Show less

We're in search of a seasoned ML Engineer to spearhead innovative projects as an individual contributor. You’ll get to dive deep into cutting-edge technology where you'll tinker with LLMs and Agents for enterprises, building autonomous Agents leveraging best in class LLMs, Agentic RAGs and incept new workflow automation systems. You will be responsible for developing production-ready inference pipelines, managing model deployment and versioning, and ensuring effective validation processes. You'll also be working hand in hand with cross-functional teams in product and engineering to shape our machine learning products, bringing a synthesis of innovation and pragmatism, while ensuring alignment with customer interests and best practices. Required Qualifications 8+ years of work experience Bachelors/Masters/PhD in Computer science Deep expertise working as a machine learning engineer or similar role, focusing on NLP. LLMs and related tooling: e.g. RAGs, Agents Demonstrated experience building, evaluating and testing machine learning models Led deploying and managing ML models in a production setting Strong programming skills with proven experience implementing Python-based solutions using good software engineering design practices Experience designing and evaluating ML A/B tests Previous experience at a high-growth, fast-paced VC-backed startup, or tech lead position at a larger organization Post Sales Tooling Market is Ripe for Disruption Our vision is to be the only AI platform needed for every B2B Customer Workflow. Recent advances in LLMs (Large Language Models) enable combining unstructured data generated from multi-channel customer engagements (zoom calls, email, support tickets etc.), with product usage data to generate unique insights. Statisfy’s Customer Agent automates large parts of customer engagement and creates healthy, growing customers. We are going after a massive market opportunity to replace existing legacy applications, consolidate post-sales tooling budgets with an AI-Native approach, and make Account Managers, Customer Success Managers and Technical Account Managers at B2B companies more efficient and effective. The Opportunity We are initially targeting a $1B+ North America Addressable Market comprising B2B Software Companies. Subsequently, we will pursue +$1B opportunity in Europe/APAC. Why Statisfy Statisfy is not just another startup. It is founded by 2X entrepreneur, Munish Gandhi, who raised over $70M for his previous start-up Productiv and Navin Agarwal, who was the founding engineer at The Yes, a start-up acquired by Pinterest for $300M+ within 5 years of its founding. The inspiration for Statisfy came from Munish’s experience leading the post-sales function at his previous company Productiv. Munish found that most Post-Sales leaders were frustrated with the lack of standardized post-sales processes and ineffective tools to drive team productivity and business results. Munish’s insights around building the right post-sales processes and tooling combined with Navin's deep expertise in machine learning across large data-sets, makes them the perfect founding team to pursue Statisfy’s vision. Backed by Emergent and Tau Ventures (premium Early Stage VC firms) and Founders of several AI first companies including Eightfold, Regie, Olto and Vareto, Statisfy has the vision, the expertise, and the financial backing to disrupt the post-sales tooling market. Working at Statisfy We are a mission and values-driven company. Our core values define how we operate, how we prioritize, and how we relate to each other. We are on a mission to drive transformative industry-level change. We are decisive, deliberate and accountable. We are customer-obsessed, empathetic individuals who live up to the highest ethical standards. Above all, we are humble and seek joy and camaraderie at work. And we are remote first. Come join us and jam with us! Show more Show less

Designation: - ML / MLOPs Engineer Location: - Noida (Sector- 132) Key Responsibilities: • Model Development & Algorithm Optimization : Design, implement, and optimize ML models and algorithms using libraries and frameworks such as TensorFlow , PyTorch , and scikit-learn to solve complex business problems. • Training & Evaluation : Train and evaluate models using historical data, ensuring accuracy, scalability, and efficiency while fine-tuning hyperparameters. • Data Preprocessing & Cleaning : Clean, preprocess, and transform raw data into a suitable format for model training and evaluation, applying industry best practices to ensure data quality. • Feature Engineering : Conduct feature engineering to extract meaningful features from data that enhance model performance and improve predictive capabilities. • Model Deployment & Pipelines : Build end-to-end pipelines and workflows for deploying machine learning models into production environments, leveraging Azure Machine Learning and containerization technologies like Docker and Kubernetes . • Production Deployment : Develop and deploy machine learning models to production environments, ensuring scalability and reliability using tools such as Azure Kubernetes Service (AKS) . • End-to-End ML Lifecycle Automation : Automate the end-to-end machine learning lifecycle, including data ingestion, model training, deployment, and monitoring, ensuring seamless operations and faster model iteration. • Performance Optimization : Monitor and improve inference speed and latency to meet real- time processing requirements, ensuring efficient and scalable solutions. • NLP, CV, GenAI Programming : Work on machine learning projects involving Natural Language Processing (NLP) , Computer Vision (CV) , and Generative AI (GenAI) , applying state-of-the-art techniques and frameworks to improve model performance. • Collaboration & CI/CD Integration : Collaborate with data scientists and engineers to integrate ML models into production workflows, building and maintaining continuous integration/continuous deployment (CI/CD) pipelines using tools like Azure DevOps , Git , and Jenkins . • Monitoring & Optimization : Continuously monitor the performance of deployed models, adjusting parameters and optimizing algorithms to improve accuracy and efficiency. • Security & Compliance : Ensure all machine learning models and processes adhere to industry security standards and compliance protocols , such as GDPR and HIPAA . • Documentation & Reporting : Document machine learning processes, models, and results to ensure reproducibility and effective communication with stakeholders. Required Qualifications: • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field. • 3+ years of experience in machine learning operations (MLOps), cloud engineering, or similar roles. • Proficiency in Python , with hands-on experience using libraries such as TensorFlow , PyTorch , scikit-learn , Pandas , and NumPy . • Strong experience with Azure Machine Learning services, including Azure ML Studio , Azure Databricks , and Azure Kubernetes Service (AKS) . • Knowledge and experience in building end-to-end ML pipelines, deploying models, and automating the machine learning lifecycle. • Expertise in Docker , Kubernetes , and container orchestration for deploying machine learning models at scale. • Experience in data engineering practices and familiarity with cloud storage solutions like Azure Blob Storage and Azure Data Lake . • Strong understanding of NLP , CV , or GenAI programming, along with the ability to apply these techniques to real-world business problems. • Experience with Git , Azure DevOps , or similar tools to manage version control and CI/CD pipelines. • Solid experience in machine learning algorithms , model training , evaluation , and hyperparameter tuning Show more Show less

Job title: Listening/Survey Research Analyst Location : Hyderabad About The Job At Sanofi we chase the miracles of science to improve people’s lives. We are dedicated to making a positive impact on the lives of the patients and families we serve, and we accomplish our goals through world-class research and with the compassion and commitment of our employees. As we continue to transform the practice of medicine, the next chapter of Sanofi’s Play to Win strategy will require a focus on delivering transformation and simplification of our core processes, optimizing resource allocation and deployment to fuel business growth and investment in science. To facilitate this transformation, a new Business Operations Business Unit is being established, bringing together existing business service activities, and driving further expansion of centralized services at scale into a global unit, with a focus on driving simplification, efficiency, and productivity. We are seeking a highly skilled Listening/Survey Research Analyst to join our dynamic Master Data Management Team. This role is crucial in driving our understanding of employee experiences and enhancing our engagement strategies. The ideal candidate will have extensive training in quantitative research, expertise in survey question design best practices, and the ability to translate HR data collection into actionable insights. In this role, you will design, configure, and manage employee listening surveys to capture insights that drive organizational improvement. You will also maintain online dashboards that convey findings and democratize the organization’s understanding of employee engagement levels. You will collaborate with stakeholders and program leaders to ensure surveys are aligned with strategic goals, analyze results, and deliver actionable insights. This is a critical role in enhancing employee engagement and fostering a data-driven culture. Main Responsibilities Design and configure surveys using listening technologies such as Peakon, Qualtrics, or similar systems. Develop and refine survey questions to accurately measure employee opinions, experiences, and behaviors. Test and troubleshoot surveys to ensure functionality and user experience. Utilize statistical techniques to analyze data and identify trends, patterns, and correlations in employee listening datasets. Provide issue resolution to current survey errors and trouble shoot with P&C stakeholders Act as the primary contact point for survey-related inquiries from internal teams. Partner with People and Culture to interpret survey results and develop strategies for improvement. Ensure data accuracy, integrity, and compliance with organizational policies and regulatory requirements. Maintain confidentiality when handling sensitive employee data. Monitor the effectiveness of surveys and recommend enhancements for future iterations. Stay updated on best practices in employee listening strategies and survey methodologies. About You Experience: 2+ years of experience in survey configuration. Workday Peakon Employee Voice Fundamentals required. Demonstrated proficiency in survey platforms such as Peakon or Qualtrics. Excellent project management skills with the ability to manage multiple tasks simultaneously. Soft skills & Technical skills: Advanced skills in statistical software (e.g., SPSS, R, Python) and data visualization tools (e.g., Tableau, Power BI). Strong analytical and problem-solving skills, with the ability to assess complex situations and recommend effective solutions. Strong communication skills to present complex data insights in a clear and concise manner. Strong interpersonal skills, with the ability to build relationships and work effectively within cross-functional teams. Strong quantitative research skills, including statistical testing, causal inference, and A/B testing methodologies Education: Bachelor’s degree in business administration, Information Technology, Human Resources, or a related field. Languages: Fluent in English (spoken and written) null Show more Show less

Position Summary... What you'll do... Role: Staff, Data Scientist Experience: 8- 15 years Location: Chennai About EBS team: Enterprise Business Services is invested in building a compact, robust organization that includes service operations and technology solutions for Finance, People, Associate Digital Experience. Our team is responsible for design and development of solution that knows our consumers needs better than ever by predicting what they want based on unconstrained demand, and efficiently unlock strategic growth, economic profit, and wallet share by orchestrating intelligent, connected planning and decisioning across all functions. We interact with multiple teams across the company to provide scalable robust technical solutions. This role will play crucial role in overseeing the planning, execution and delivery of complex projects within team Walmarts Enterprise Business Services (EBS) is a powerhouse of several exceptional teams delivering world-class technology solutions and services making a profound impact at every level of Walmart. As a key part of Walmart Global Tech, our teams set the bar for operational excellence and leverage emerging technology to support millions of customers, associates, and stakeholders worldwide. Each time an associate turns on their laptop, a customer makes a purchase, a new supplier is onboarded, the company closes the books, physical and legal risk is avoided, and when we pay our associates consistently and accurately, that is EBS. Joining EBS means embarking on a journey of limitless growth, relentless innovation, and the chance to set new industry standards that shape the future of Walmart. About Team The data science team at Enterprise Business Services Pillar at Walmart Global Tech focuses on using the latest research in machine learning, statistics, and optimization to solve business problems. We mine data, distill insights, extract information, build analytical models, deploy Machine Learning algorithms, and use the latest algorithms and technology to empower business decision-making. In addition, we work with engineers to build reference architectures and machine learning pipelines in a big data ecosystem to productize our solutions. Advanced analytical algorithms driven by our team will help Walmart to optimize business operations, business practices and change the way our customers shop. The data science community at Walmart Global Tech is active in most of the Hack events, utilizing the petabytes of data at our disposal, to build some of the coolest ideas. All the work we do at Walmart Labs will eventually benefit our operations ; our associates, helping Customers Save Money to Live Better. What You Will Do As a Staff Data Scientist for Walmart Global Tech, you'll have the opportunity to Drive data-derived insights across a wide range of retail ; Finance divisions by developing advanced statistical models, machine learning algorithms and computational algorithms based on business initiatives Direct the gathering of data, assess data validity and synthesize data into large analytics datasets to support project goals Utilize big data analytics and advanced data science techniques to identify trends, patterns, and discrepancies in data. Determine additional data needed to support insights Build and train AI/ML models for replication for future projects Deploy and maintain the data science solutions Communicate recommendations to business partners and influence future plans based on insights Consult with business stakeholders regarding algorithm-based recommendations and be a thought-leader to develop these into business actions. Closely partners with the Senior Manager ; Director of Data Science to drive data science adoption in the domain Guides. data scientists, senior data scientists ; staff data scientists across multiple sub-domains to ensure on-time delivery of ML products Drive efficiency across the domain in terms of DS and ML best practices, ML Ops practices, resource utilization, reusability and multi-tenancy. Lead multiple complex ML products and guide senior tech leads in the domain in efficiently leading their products. Drive synergies across different products in terms of algorithmic innovation and sharing of best practices. Proactive identification of complex business problems that can be solved using advanced ML, finding opportunities and gaps in the current business domain Evaluates proposed business cases for projects and initiatives What You Will Bring Masters with > 10 years OR Ph.D. with > 8 years of relevant experience. Educational qualifications should be Computer Science/Statistics/Mathematics or a related area. Minimum 6 years of experience as a data science technical lead Ability to lead multiple data science projects end to end. Deep experience in building data science solution in areas like fraud prevention, forecasting, shrink and waste reduction, inventory management, recommendation, assortment and price optimization Deep experience in simultaneously leading multiple data science initiatives end to end – from translating business needs to analytical asks, leading the process of building solutions and the eventual act of deployment and maintenance of them Strong experience in machine learning: Classification models, regression models, NLP, Forecasting, Unsupervised models, Optimization, Graph ML, Causal inference, Causal ML, Statistical Learning, experimentation ; Gen-AI In Gen-AI, it is desirable to have experience in embedding generation from training materials, storage and retrieval from Vector Databases, set-up and provisioning of managed LLM gateways, development of Retrieval augmented generation based LLM agents, model selection, iterative prompt engineering and finetuning based on accuracy and user-feedback, monitoring and governance. Ability to scale and deploy data science solutions. Strong Experience with one or more of Python and R. Experience in GCP/Azure Strong Experience in Python, PySpark Google Cloud platform, Vertex AI, Kubeflow, model deployment Strong Experience with big data platforms – Hadoop (Hive, Map Reduce, HQL, Scala) Experience with GPU/CUDA for computational efficiency About Walmart Global Tech Imagine working in an environment where one line of code can make life easier for hundreds of millions of people. That’s what we do at Walmart Global Tech. We’re a team of software engineers, data scientists, cybersecurity expert's and service professionals within the world’s leading retailer who make an epic impact and are at the forefront of the next retail disruption. People are why we innovate, and people power our innovations. We are people-led and tech-empowered. We train our team in the skillsets of the future and bring in experts like you to help us grow. We have roles for those chasing their first opportunity as well as those looking for the opportunity that will define their career. Here, you can kickstart a great career in tech, gain new skills and experience for virtually every industry, or leverage your expertise to innovate at scale, impact millions and reimagine the future of retail. Flexible, hybrid work We use a hybrid way of working with primary in office presence coupled with an optimal mix of virtual presence. We use our campuses to collaborate and be together in person, as business needs require and for development and networking opportunities. This approach helps us make quicker decisions, remove location barriers across our global team, be more flexible in our personal lives. Benefits Beyond our great compensation package, you can receive incentive awards for your performance. Other great perks include a host of best-in-class benefits maternity and parental leave, PTO, health benefits, and much more. Belonging We aim to create a culture where every associate feels valued for who they are, rooted in respect for the individual. Our goal is to foster a sense of belonging, to create opportunities for all our associates, customers and suppliers, and to be a Walmart for everyone. At Walmart, our vision is "everyone included." By fostering a workplace culture where everyone is—and feels—included, everyone wins. Our associates and customers reflect the makeup of all 19 countries where we operate. By making Walmart a welcoming place where all people feel like they belong, we’re able to engage associates, strengthen our business, improve our ability to serve customers, and support the communities where we operate. Equal Opportunity Employer Walmart, Inc., is an Equal Opportunities Employer – By Choice. We believe we are best equipped to help our associates, customers and the communities we serve live better when we really know them. That means understanding, respecting and valuing unique styles, experiences, identities, ideas and opinions – while being inclusive of all people. Minimum Qualifications... Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications. Minimum Qualifications:Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years' experience in an analytics related field. Option 3: 6 years' experience in an analytics or related field. Preferred Qualifications... Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications. Primary Location... Rmz Millenia Business Park, No 143, Campus 1B (1St -6Th Floor), Dr. Mgr Road, (North Veeranam Salai) Perungudi , India R-2182242 Show more Show less

About the job A little about us... LTIMindtree is a global technology consulting and digital solutions company that enables enterprises across industries to reimagine business models, accelerate innovation, and maximize growth by harnessing digital technologies. As a digital transformation partner to more than 750 clients, LTIMindtree brings extensive domain and technology expertise to help drive superior competitive differentiation, customer experiences, and business outcomes in a converging world. Powered by nearly 90,000 talented and entrepreneurial professionals across 35 countries, LTIMindtree — a Larsen & Toubro Group company — combines the industry-acclaimed strengths of erstwhile Larsen and Toubro Infotech and Mindtree in solving the most complex business challenges and delivering transformation at scale. For more info, please visit www.ltimindtree.com Job Details- We are having a weekend drive for the requirement of a Data Scientist at our Bangalore office. Date - 14th June Experience - 4 to 12 Yrs. Location – LTIMindtree Office Bangalore Whitefield Notice Period - Immediate to 60 Days only Mandatory Skills- Gen-AI, Data Science, Python, RAG and Cloud (AWS/Azure) Secondary - (Any) - Machine Learning, Deep Learning, ChatGPT, Langchain, Prompt, vector stores, RAG, llama, Computer vision, Deep learning, Machine learning, OCR, Transformer, regression, forecasting, classification, hyper parameter tunning, MLOps, Inference, Model training, Model Deployment Generic JD : More than 6 years of experience in Data Engineering, Data Science and AI / ML domain Excellent understanding of machine learning techniques and algorithms, such as GPTs, CNN, RNN, k-NN, Naive Bayes, SVM, Decision Forests, etc. Experience using business intelligence tools (e.g. Tableau, PowerBI) and data frameworks (e.g. Hadoop) Experience in Cloud native skills. Knowledge of SQL and Python; familiarity with Scala, Java or C++ is an asset Analytical mind and business acumen and Strong math skills (e.g. statistics, algebra) Experience with common data science toolkits, such as TensorFlow, KERAs, PyTorch, PANDAs, Microsoft CNTK, NumPy etc. Deep expertise in at least one of these is highly desirable. Experience with NLP, NLG and Large Language Models like – BERT, LLaMa, LaMDA, GPT, BLOOM, PaLM, DALL-E, etc. Great communication and presentation skills. Should have experience in working in a fast-paced team culture. Experience with AIML and Big Data technologies like – AWS SageMaker, Azure Cognitive Services, Google Colab, Jupyter Notebook, Hadoop, PySpark, HIVE, AWS EMR etc. Experience with NoSQL databases, such as MongoDB, Cassandra, HBase, Vector databases Good understanding of applied statistics skills, such as distributions, statistical testing, regression, etc. Should be a data-oriented person with analytical mind and business acumen. Show more Show less

Position: AI/ML Engineer (VFX Workflow & Infrastructure) Location: Hyderabad, India Role Overview The AI/ML Engineer will spearhead the development and integration of artificial intelligence and machine learning solutions into our VFX production pipeline. You’ll work closely with pipeline developers, production managers, and creative teams to reimagine workflows, automate repetitive tasks, and push the boundaries of innovation in photorealistic rendering, stylized animation, and other CGI processes. This role combines deep technical expertise with a strong understanding of the demands of a fast-paced VFX/animation studio. Key Responsibilities AI Strategy & Roadmap: Develop and maintain a strategic plan for implementing AI/ML across the VFX pipeline—covering data wrangling, rendering, asset management, animation, and post-production. Identify new approaches to innovate current workflows to increase efficiency and cut down on time. Algorithm & Model Development: Research, design, and implement ML models (e.g., computer vision, generative models, style transfer) that improve artist efficiency, production speed, enhance image quality, or enable new creative possibilities. Optimize models for performance on local GPU/CPU clusters or cloud-based infrastructures. Pipeline Integration & Automation: Collaborate with pipeline engineers to seamlessly integrate AI agents or tools into existing software stacks (e.g., Maya, Houdini, Nuke), ensuring minimal disruption to artists’ workflows. Develop automated solutions for tasks like rotoscoping, clean-up, crowd simulation, environment generation, or facial capture/animation. Infrastructure & Tooling: Architect and maintain robust data pipelines, ensuring the secure collection and organization of high-quality datasets for training AI models. Evaluate and deploy containerization/MLOps tools (Docker, Kubernetes, MLflow, etc.) for scalable model training, inference, and monitoring. Performance Optimization: Profile model performance, memory usage, and render times; implement optimizations in frameworks such as TensorFlow, PyTorch, or custom GPU pipelines. Work with DevOps/IT teams to configure and manage dedicated GPU farms or cloud compute resources. Research & Development: Stay updated with state-of-the-art ML/DL techniques, particularly in generative AI, computer vision, and real-time rendering. Introduce emerging methods (e.g., stable diffusion, large language models, neural rendering) to innovate new production techniques. Documentation & Reporting: Create clear technical documentation for AI solutions, ensuring maintainability and scalability. Present progress, insights, and ROI to executive leadership, project stakeholders, and cross-functional teams. Qualifications & Skills Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field. A PhD is a bonus but not mandatory. 5+ years of professional experience in applied machine learning or data science, with at least 2 years in a lead/managerial role. Previous experience in VFX, animation, gaming, or related entertainment industries is a bonus. Programming: Expert-level Python (C++ is a plus). ML Frameworks: Deep understanding of TensorFlow, PyTorch, scikit-learn, or similar libraries. Computer Vision & Generative Models: Familiarity with CNNs, GANs, autoencoders, stable diffusion, or neural radiance fields. Pipeline Tools: Experience with integration in VFX software (Maya, Houdini, Nuke) and plugin APIs.[Optional] DevOps & MLOps: Comfortable with containerization (Docker), orchestration (Kubernetes), CI/CD, and cloud platforms (AWS, Azure, GCP). Proven track record of translating production challenges into AI/ML solutions that deliver measurable efficiency gains or cost savings. Experience with model optimization (quantization, pruning) and GPU/CPU performance tuning. Collaboration: Excellent communication to bridge technical and creative teams, explaining complex concepts in clear, accessible language. Leadership: Ability to mentor junior engineers and foster a culture of experimentation and continuous learning. Agility: Adapts quickly to evolving project needs, production pipelines, and new AI techniques. A genuine interest in cinema, animation, or gaming—a plus if you have prior knowledge of the Baahubali IP or similar large-scale IPs. Creativity in applying AI to artistic challenges, from photorealistic digital humans to stylized animated sequences. What We Offer Impactful Role: Shape the future of VFX and animation filmmaking and leave a lasting mark on flagship studio projects. Career Growth: Lead a growing AI team, collaborate with top-tier VFX artists, and gain exposure to cutting-edge tech. Competitive Compensation: Salary, benefits, and potential for performance-based bonuses. Innovative Environment: Access to advanced hardware, robust R&D budget, and the opportunity to experiment with emerging AI trends. Show more Show less