14 Feature Engineering Jobs

Looking for a highly skilled Senior Machine Learning Engineering Lead to oversee and drive machine learning initiatives focusing on time series analysis, process curve analysis, tabular data, and feature engineering. In this role, you will lead a team of engineers and data scientists, ensuring the effective delivery of machine learning solutions to customers. You will also be responsible for designing efficient workflows, building robust CI/CD pipelines, and handling client interactions to deliver high-quality solutions on time.Roles & Responsibilities: Machine Learning and Data Engineering: Time Series Analysis : Develop and implement advanced machine learning models for analyzing time-series data (e.g., forecasting, anomaly detection). Process Curve Analysis : Apply machine learning techniques to analyze process curves, optimize processes, and predict system behavior based on historical data. Tabular Data : Manage and work with structured/tabular datasets to build models that deliver actionable insights. Feature Engineering : Design and implement innovative feature engineering techniques to enhance model performance, ensuring that features align with business goals. Model Development and Optimization : Develop, test, and optimize machine learning models and algorithms for various business use cases. Leadership and Team Management: Team Mentorship : Lead a team of machine learning engineers and data scientists, providing guidance and mentorship to junior team members. Collaboration : Work closely with data scientists, software engineers, product managers, and other stakeholders to design, implement, and deliver end-to-end solutions. Customer Handling : Serve as the primary point of contact for customers, gathering requirements, addressing technical challenges, and ensuring the timely delivery of high-quality solutions. Client Deliverables : Ensure all project milestones are met, and machine learning models and solutions are aligned with customer expectations. Pipeline and Workflow Design: CI/CD Pipeline : Design and maintain robust CI/CD pipelines for machine learning model training, validation, and deployment, ensuring efficient and automated workflows. Model Deployment and Monitoring : Oversee the deployment of machine learning models into production, ensuring they meet performance, reliability, and scalability requirements. Automated Workflows : Build automated workflows for data pipelines, model training, evaluation, and reporting, ensuring seamless integration with business processes. Quality Assurance and Optimization: Performance Monitoring : Monitor model performance post-deployment, identifying and addressing any issues related to accuracy, speed, or scalability. Process Improvement : Continuously evaluate and improve model development practices, machine learning pipelines, and workflows to drive efficiency and reduce time-to-market. Documentation : Ensure that all models, pipelines, and processes are well-documented and easily reproducible for future iterations or modifications. Required skills:Technical Skills: Programming Languages : Proficiency in Python, R, or other relevant languages (e.g., Java, Scala). Machine Learning Frameworks : Expertise in ML libraries like scikit-learn, TensorFlow, Keras, XGBoost, PyTorch, etc. Time Series Analysis : Experience with time-series forecasting models (ARIMA, LSTM, Prophet, etc.) and anomaly detection. Data Engineering : Expertise in working with large-scale datasets and tools like Pandas, NumPy, SQL, and data wrangling techniques. Feature Engineering : Strong skills in creating meaningful features to improve model accuracy and performance. CI/CD Tools : Experience with CI/CD tools like Jenkins, GitLab, CircleCI, or similar platforms for automating deployment workflows. Cloud Platforms : Experience with cloud computing services like AWS, GCP, or Azure for model deployment and scalability. Version Control : Proficient in using Git for version control and collaboration. Soft Skills: Strong leadership and team management skills, with a focus on mentoring and development of team members. Excellent communication skills for handling customer interactions, explaining technical concepts to non-technical stakeholders, and delivering presentations. Problem-solving mindset with the ability to analyze complex data and identify actionable insights. Highly organized, detail-oriented, and able to manage multiple projects simultaneously. Experience: 8+ years of experience in machine learning engineering with a focus on time-series analysis, process curve analysis, tabular data, and feature engineering. At least 3-5 years of leadership experience managing teams and handling customer-facing responsibilities. Strong experience in designing and deploying ML models in production environments. Proven track record of successfully managing client relationships and delivering high-quality solutions on time. Experienced in working in cross-functional, international setups Entrepreneurial, business-driven mindset. Preferred Expertise: Experience in deploying models at scale using containerization technologies like Docker and Kubernetes. Knowledge of MLOps principles and practices. Background in domain-specific areas (e.g., manufacturing, finance, healthcare) related to time-series and process data. Qualifications B.E./ M.E./M. Tech in Computer Science Engineering, Ph. D is plus

About Us: At Novus Loyalty, we are committed to building cutting-edge AI-driven solutions that enhance business performance and user experience. We are currently seeking a skilled and passionate AI Engineer to join our team, with a strong emphasis on Azure AI technologies. Key Responsibilities: Design, develop, and deploy AI models using Azure AI services. Work on various AI domains, including Generative AI, Agentic AI, and other advanced ML models. Collaborate with cross-functional teams to integrate AI solutions into production environments. Conduct data analysis and preprocessing to support model development. Monitor and optimize AI model performance and accuracy. Stay up-to-date with emerging AI technologies, tools, and best practices. Required Qualifications: Minimum 3 years of hands-on experience in AI/ML model development. Proven experience with Azure AI services (e.g., Azure Machine Learning, Cognitive Services, Azure OpenAI). Strong programming skills in Python or other relevant languages. Solid understanding of machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with large language models (LLMs), NLP, or generative AI applications is a plus. Familiarity with MLOps practices and cloud-based model deployment. Excellent problem-solving and communication skills.

Oracle Cloud Infrastructure (OCI) is at the forefront of cloud innovation, blending the agility of a startup with the reliability of a leading enterprise software provider Our AI Science team pioneers state-of-the-art machine learning solutions that empower customers and solve complex real-world problems at scale. provider. As a Senior Applied Scientist, you will develop and deploy state-of-the-art computer vision solutions leveraging generative AI technologies such as Large multimodal models and computer vision technologies such as image classification, object detection, vision grounding etc. This individual contributor(IC) role will build best-in-class computer vision solutions at scale. Perfect for a hands-on data science architecture design and is eager to drive innovation and excellence in AI and computer vision area. You will partner with the Product and Engineering managers to influence strategic decisions, drive experimentation and communicate results to higher managements. You will build best-in-class LLM/LMM/computer vision solutions for the Oracle business domain at scale. You will also partner with Product Management, Data Labelling and Engineering teams to get to develop build best-in-class computer vision solutions at scale. The ideal candidate has extensive experience with computer vision techniques, deep learning techniques, model serving, and a demonstrated ability to think strategicallyabout business, product, and technical challenges to contribute to the development of current and future vision services Key Responsibilities Development of advanced AI models and algorithms, focusing on large language model, large multimodal, computer vision and foundation models. Design, implement and test the critical module/features of AI service that are correct, highly available, scalable, and cost-effective. Champion best practices for testing, benchmarking, and model validation to ensure reliability and performance. Analysis of ML models, and optimizing models for accuracy and latency. Large-scale training & production deployment with ML models. Own data analysis, feature engineering, technique selection & implementation, debugging, and maintenance of production model. Experience implementing machine learning algorithms or research papers from scratch to production. Work with large, complex data sets. Proactively identify the technical issues/bugs and provide innovative solutions. File patent and publication as by product of solving complex business problems Partner closely with product managers, engineering leads, and annotation/data teams to define requirements, data quality assurance and acceptance of data/annotation as required. Leverage Oracle Cloud technology. Preferred Qualifications Ph.D. (preferred) or Master's in Computer Science, Machine Learning, Computer Vision, or related field. PhD in computer vision or 2+ years of Experience designing, implementing and deploying computer vision models in production environments Expertise in GenAI, LLMs, LMMs, object detection, facial recognition, and image classification. Strong foundation in deep learning architectures such as CNNs, transformers, diffusion models, and multimodal models. Expert in at least one high level language such as Python/Java/C++ Practical experience in ML algorithm design, model training and production deployment using microservices architecture Practical experience working in a cloud environment: Oracle Cloud (OCI), AWS, GCP, Azure or similar technology. Experience or willingness to learn and work in Agile and iterative development processes. Strong drive to learn and master new technologies and techniques. Deep understanding of data structures, algo Career Level - IC3

Job Requirements Education: Bachelors degree (Statistics, Business Analytics, Data Science, Math, Economics, etc.) Masters degree preferred (MBA/MS/M.Tech in Computer Science or related field) Experience: 5–7 years in a Data Science/Advanced Analytics role Behavioral Skills: Delivery Excellence Business Orientation Social Intelligence Innovation and Agility Knowledge & Technical Skills: Functional analytics experience (Supply Chain, Marketing, Customer Analytics, etc.) Statistical modeling using tools such as R, Python, KNIME Knowledge of statistics and experimental design (A/B testing, hypothesis testing, causal inference) Experience building and evaluating machine learning models MLOps tools and practices (MLflow, DVC, Docker, etc.) Strong Python programming (Pandas, Scikit-learn, PyTorch/TensorFlow, etc.) Experience with big data technologies (AWS, Azure, GCP, Hadoop, Spark) Familiarity with relational (MySQL, SQL Server) and non-relational (MongoDB, DynamoDB) databases BI and reporting tools (Power BI, Tableau, Alteryx) Proficiency with Microsoft Office applications (especially Excel) Roles & Responsibilities Analytics & Strategy: Analyze large-scale structured and unstructured data to develop insights and machine learning models across various business domains Apply statistical and machine learning techniques to generate value from operational, financial, and customer data Recommend best-fit algorithms and models with clear justifications for business use Leverage cloud platforms for modeling and big data analysis; utilize data visualization tools to communicate results Operational Excellence: Follow industry-standard coding practices and development lifecycles Formulate hypotheses, develop analytics frameworks, and bring structure to complex problems Collaborate with Data Engineering to maintain core data infrastructure and automate analytical processes Stakeholder Engagement: Work cross-functionally with business stakeholders, engineers, and visualization experts to deliver impactful projects Communicate complex models and results to non-technical stakeholders in a clear and compelling way

Requirements: Must have experience as a Data Scientist or transitioned from Data Engineer Proficient in AWS Expertise in ML Model Design & Development Strong Feature Engineering experience Good to Have: NLP, GraphQL / Graph ML, Generative AI Education: B.Tech / M.Tech in Computer Science, IT, or ECE Location: Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

Build and deploy scalable ML models and MLOps pipelines in collaboration with data scientists Required Candidate profile 6–12 yrs in ML development, Python, model tuning, and enterprise AI deployment.

We are looking for a skilled professional with strong AI Enabled Automation skills and interest in applying AI in the process automation space. The ideal candidate will have 9 to 13 years of relevant experience. This position is based in Bengaluru. ### Roles and Responsibility Develop and implement AI enabled automation solutions aligned with business objectives. Design and deploy Proof of Concepts (POCs) and Points of View (POVs) across various industry verticals, demonstrating the potential of AI enabled automation applications. Ensure seamless integration of optimized solutions into the overall product or system. Collaborate with cross-functional teams to understand requirements and integrate solutions into cloud environments. Educate team members on best practices and stay updated on the latest tech advancements to bring innovative solutions to projects. Work closely with stakeholders to identify opportunities for process improvements and implement changes using AI technologies. ### Job Requirements Proficiency in Python and frameworks like PyTorch, TensorFlow, Hugging Face Transformers. Strong foundation in ML algorithms, feature engineering, and model evaluation. Experience with Deep Learning, Neural Networks, RNNs, CNNs, LSTMs, Transformers (BERT, GPT), and NLP. Experience in GenAI technologies such as LLMs (GPT, Claude, LLaMA), prompting, fine-tuning. Knowledge of retrieval augmented generation (RAG) and knowledge graph RAG. Experience with multi-agent orchestration, memory, and tool integrations. Experience implementing MLOps practices and tools (CI/CD for ML, containerization, orchestration, model versioning, and reproducibility). Experience with cloud platforms (AWS, Azure, GCP) for scalable ML model deployment. Good understanding of data pipelines, APIs, and distributed systems. Build observability into AI systems – latency, drift, performance metrics. Strong written and verbal communication, presentation, client service, and technical writing skills in English for both technical and business audiences. Strong analytical, problem-solving, and critical thinking skills. Ability to work under tight timelines for multiple project deliveries.

We are looking for a highly skilled and experienced AI Engineer with 2 to 7 years of experience to join our team in Bengaluru. The ideal candidate will have a strong background in artificial intelligence, machine learning, and software engineering. ### Roles and Responsibility Design, develop, and deploy AI models and systems that align with business objectives. Conduct data analysis, pre-processing, and feature engineering to ensure high-quality input for AI algorithms. Train, evaluate, and optimize AI models using various machine learning algorithms and techniques. Implement scalable and efficient AI solutions in production environments, considering performance, latency, and reliability. Collaborate with AI and software engineers to integrate AI models into production systems and monitor their performance. Analyze and interpret AI model outputs, providing insights and recommendations to stakeholders. ### Job Requirements Deep understanding of AI and machine learning algorithms, including regression, classification, clustering, and deep learning. Proficiency in Python for AI model development, along with experience in deep learning frameworks such as TensorFlow, PyTorch, or Keras. Familiarity with cloud platforms, preferably Azure, to deploy scalable AI solutions, and knowledge of distributed computing frameworks like Spark. Strong foundation in software engineering practices, including version control with Git, testing, documentation, and code review. Understanding of NLP techniques and frameworks such as Hugging Face's Transformers, BERT, GPT, or Transformer models, TensorFlow's NLP library, or spaCy for language-related AI applications. Experience with natural language processing (NLP) techniques and frameworks, and generative AI techniques, including prompt engineering and fine-tuning LLMs. Proficiency in data pre-processing, visualization, SQL, and big data technologies, along with strong skills in Python for AI model development and implementation. Knowledge of containerization tools like Docker and an understanding of responsible AI practices and data privacy. Generative AI Techniques: Knowledge and experience in Generative AI techniques, prompt engineering, vector database, LLMs such as OpenAI, Azure OpenAI, Open-source LLMs. Fine-tuning: Collaborate with the research and development teams to fine-tune large language models using prompts, ensuring the models produce accurate, contextually relevant, and safe responses. Model Evaluation and Optimization: Experience with model evaluation, hyperparameter tuning, and optimization techniques. Data Pre-processing and Visualization: Solid understanding of techniques for data pre-processing, feature engineering, and data visualization. Cloud Platforms: Familiarity with cloud platforms like AWS, Azure, or GCP for scalable AI solutions. (Azure preferred) Distributed Computing: Knowledge of distributed computing frameworks, particularly Spark, for large-scale data processing. Version Control Systems: Proficient in using version control systems like Git for collaborative AI development. Troubleshooting and Debugging: Ability to troubleshoot and debug complex AI systems and models. Containerization: Knowledge of containerization tools like Docker for efficient deployment of AI solutions. Software Engineering Practices: Familiarity with software engineering practices, including testing, documentation, and code review.

Practice Overview : Skill/Operating Group Technology Consulting Level Manager Location Gurgaon/Mumbai/ Bangalore Travel Percentage Expected Travel could be anywhere between 0-100% Why Technology Consulting The Technology Consulting business within Capability Network invents the future for clients by providing them with the right guidance, design thinking and innovative solutions for technological transformation. As technology rapidly evolves, it's more important than ever to have an innovation advisor who can create a new vision or put one into place"to solve the client's toughest business problems. Specialize in management or technology consulting to transform the worlds leading organizations by building innovative business solutions as their trusted advisor by: Helping Clients :Rethinking IT and Digital ecosystems and innovating to help clients keep pace with fast-changing, customer-driven environments. Enhancing your Skillset :Building expertise and innovating with leading-edge technologies such as Blockchain, Artificial Intelligence and Cloud. Transforming Businesses :Developing customized, next-generation products and services that help clients shift to new business models designed for todays connected"landscape of disruptive technologies Principal Duties And Resp o nsibilities: Working closely with our clients, consulting professionals design, architect, build and implement strategies, POC that can help enhance business performance. Develop specialized expertise "strategic, industry, functional, technical"in a diverse project environment that offers multiple opportunities for career growth." The opportunities to make a difference within exciting client initiatives are limitless in this ever-changing business landscape. Here are just a few of your day-to-day responsibilities. Identifying , Assessing and solving"complex business problems"for area of responsibility , where analysis of situations or data requires an in-depth evaluation of variable factors. Interact with client stakeholders to understand their AI problems, priority use-cases, define a problem statement, understand the scope of the engagement, and also drive projects to deliver value to the client Understand client's business and IT goals, vision and identify opportunities for reinvestment Through your expertise and experience, guide your team to suggest the right solutions to meet the needs of clients and help draw up practical implementation road maps that position them for long-term success Benchmark against global research benchmarks and leading industry peers to understand current & recommend AI solutions Conduct discovery workshops and design sessions to elicit AI opportunities & client pain areas. Technical SME to design & guide development of E nterprise wide AI architecture & strategy Managing multi-disciplinary teams to shape, sell, communicate and implement programs Contribute towards practice development initiatives like new offering development, people management etc Mentoring and People skill development Qualifications Qualifications: MBA Degree from Tier-1 College (Preferable) Bachelors Degree AI/ML/Cloud AI Certifications preferred Minimum of 10-15 years large scale consulting experience and managing teams in a consulting environment or at high tech companies Experience: We are looking for Advanced Analytics and AI Managers to join our growing team having experience with Machine learning and NLP applications . Operating across all stages of the innovation spectrum, with a remit to build the future in real-time. Experience in designing and building end-to-end AI Strategy & solutions using Cloud & Non-Cloud AI ML, NLP algo. Assessment: Works as part of multi-disciplinary teams and responsible for independently driving specific AI workstreams through collaboration with designers, other AI team members, platform & Data engineers, business subject matter experts and technology delivery teams to assess AI potential and develop use cases. Liaises effectively with global community and senior leadership to identify and drive value opportunities around AI, support investments in POCs, pilots and chargeable projects. Design: The Managers role on these projects centers around independently executing workstreams around the application of analytics, data science and advanced cognitive methods to derive insights & actions from data and develop POCs and appropriate high-level scalable solution designs . Strong expertise in designing AutoML , MLOps AI solutions using any of the Cloud services (AWS, GCP, Azure). Architecture: The nature of these projects change as ideas and concepts mature, ranging from research, proofs -of-concept and the art-of-the-possible to the delivery of real-world applications for our clients. Focus in this area is on the impact to clients technology landscape/ architecture and ensuring formulation of relevant guiding principles and platform components. Experti s e in designing Enterprise AI strategy, Responsible AI frameworks is preferred. Strong experience handling multiple end- to-end AI Lifecycle projects from Data preparation, Modeling, Build, Train & Deploy. Product/ Framework/ Tool evaluation: Collaborate with business experts for business understanding, working with other consultants and platform engineers for solutions and with technology teams for prototyping and client implementations. Evaluate existing products and frameworks available and develop options for proposed solutions. Have an understanding of the framework/ tools to engage the client in meaningful discussions and steer towards the right recommendation . Modeling: Strong SME knowledge in Data Preparation, Feature engineering, Feature selection, Training datasets, Algorithmic selection, Optimizing & Production deployment. Work as a technical SME to teams and client on advising right AI solutions. The Manager should have practical industry expertise . The areas of Financial Services, Retail, Telecommunications, Life Sciences and Resources are of interest but experience in equivalent domains is also welcomed. Consultants should understand the key technology trends in their domain and the related business implications.

Job Description The Oracle Global Business Unit (GBU) Generative AI team is responsible for leading Generative AI and Agent needs of business applications serving variety of markets including Finance, Hospitality, Construction and Engineering, Energy & Water etc. Our goal is to enable customers to apply AI to solve their business problems with Oracle's assistance and expertise in Generative AI. In this role, you will have an opportunity to work with teams of applied scientists and engineers to deliver high quality generative ai and agent features that delights our customers with the confidence that their data are safe and protected. Your Opportunity We are seeking a Principal Applied Scientist (IC4) to spearhead Generative AI and Agent use cases that support GBU business applications as well as GBU consulting. As an applied scientist, you will be responsible for driving the development and implementation of cutting-edge technologies. We are building a core talented team specialized in Generative AI. We are looking for candidates who are passionate about building state-of-the-art technologies to solve real-world problems and have a solid technical background in deep learning, especially natural language processing (NLP) and multimodal models, to join this team. You will collaborate with a team of world-class scientists, engineers and product managers. Were looking for a person who will bring a passion for innovative products, strong collaboration skills and the ability to work closely with both development and consulting teams. Youll be a Generative AI expert who is hands-on as well as be adept at evangelizing and influencing multiple stakeholders without direct authority on best practices and to get things done efficiently. Most importantly we believe in a people-first approach. Our team consists of people from a wide variety of backgrounds, with different professional and life experiences, who support each other to build things the right way and enjoy ourselves while doing it. What we offer Being part of one of the most visionary and mission-driven organizations in Oracle, cooperating with talented peers with diverse backgrounds worldwide. High visibility to senior leadership, as well as technical leaders and partners. Opportunity to build state-of-the-art technologies in large language models and generative AI at scale. Close partnership with product managers and software engineers to deploy Generative AI features into products in various business-critical scenarios. Building performance evaluations of Generative AI systems for continuous improvement of alignment with stakeholders' growing expectations. What Youll Do Develop, implement, and optimize large language models and generative AI technologies, including training/finetuning and computation optimizations. Collaborate with software engineers to deploy LLM / Generative AI models and Agents into production environments. Stay up-to-date with the latest advancements in the field of generative AI. Collaborate with cross-functional teams to drive the development and adoption of LLM and generative AI solutions across various organizations in the company. Work directly with key customers and accompany them on their AI journey understanding their requirements, help them envision and design the right solutions and work together with their engineering and data science team to remove blockers and translate the feedback into actionable items for individual service owners. Design and build solutions and help GBU development teams reach successful pilots, PoCs and feature releases with our AI/Gen AI and DS technologies. Bring back learnings from these engagements to standardize Generative AI and Agent implementations for efficiency, scale and ease of maintenance. Support GBU consulting with re-usable solution patterns and reference solutions / showcases that can apply across multiple customers. Being enthusiastic, self-motivated, and a great collaborator. Lead patent filings and author papers to show innovative enterprise grade developments. Be our product evangelist - engage directly with customers and partners, participate and present in external events and conferences, etc. Qualifications: PhD, MS in computer science, engineering, mathematics or a field related to deep learning. Strong knowledge of ML fundamentals supervised vs unsupervised modeling, time series, highly unbalanced and noisy data sets, complex feature engineering, recommendation systems, using and optimizing gradient boosting models, NLP, deep learning on all kinds of unstructured data. 5+ (for Senior), 7+ (for Principal), 10+ (for Sr Principal) years of work experience including a minimum of 2-year experience in developing large-scale ML solutions, and in particular deep learning solutions in the NLP field. Proficiency with deep learning frameworks (such as PyTorch or TensorFlow) and deep learning architectures (especially Transformers). Hands-on experience with distributed training of large language models. Strong development experience of deep learning modeling in Python. Familiarity with the latest advancements in LLM and generative AI technologies. Familiarity with engineering best practices, including shared codebase, version control, containerization, etc. Passionate about being a builder and working with talented peers to solve hard problems at scale. Good communication skills to convey technical concepts in straightforward terms with product managers and various stakeholders. Preferred Skills Publications in top-tier deep learning conferences or significant contributions to prominent deep learning repositories Industrial experience in system design, software development, and production deployment Excel in transforming ambiguous requirements into actionable plans with deep learning techniques for problem-solving. First-hand experience with deep reinforcement learning First-hand experience with the latest technologies in LLM and generative AI such as parameter-efficient finetuning and instruction finetuning is a plus Familiarity with the latest advancements in computer vision and multimodal models is a plus Top-tier performance in prestigious deep learning leaderboards or large model-related competitions is a plus. Career Level - IC5 Responsibilities Drives and plans implementation of company policy for achieving business goals. Defines the bar for science practices, and helps teams achieve those goals. Identifies and mitigates risks across full set of systems, particularly at the intersection of business and engineering. Innovate AI and ML powered solutions (rich APIs, ML models and end to end services) with strategic ISVs and customers. Develop deep product intuition to influence future product roadmaps and drive decision making. Clearly articulate technical work to audiences of all levels and across multiple functional areas in both internal and external settings. Engage in forward looking research both internal and with academic institutions globally. Hires and mentors across the org. Perform an active role in team planning, review and retrospective events. Ensures experiments are ready for hand-off to Software Developers ship into production. May perform other duties as assigned.

Job Description About Oracle and OHAI Building off our Cloud momentum, Oracle has formed a new organization - Oracle Health & AI. This team will focus on product development and product strategy for Oracle Health, while building out a complete platform supporting modernized, automated healthcare. This is a net new line of business, constructed with an entrepreneurial spirit that promotes an energetic and creative environment. We are unencumbered and will need your contribution to make it a world class engineering center with the focus on excellence. About ODA Within the larger Oracle Health & AI organization, the Oracle Digital Assistant (ODA) is an Assistant platform that enables developers to create their own skills and digital assistants using the Conversational AI and Generative AI capabilities exposed to them in a low-code paradigm. The ODA team has been powering conversational AI experiences for all internal Oracle teams and several external customers for the past 7 years and is evolving rapidly to provide Generative AI solutions for the healthcare and enterprise domains. We operate in an agile environment with a substantial charter, high visibility, and support from senior leadership. About the team We are looking for ML scientists, Data Engineers, Software Development Engineers, Product/Program Managers and ML engineers with a strong background in machine learning to build industry-leading solutions. You will work with huge volumes of data to solve/enable solving real-world problems in the Healthcare domain that are productionized into our Health AI products. Your solutions will be productized as features in the end products. These are new teams that we are putting together in India Center from scratch and the work will span across New Feature Development for CDA Specialty Expansion & Innovation, Language & Region Expansion, Software Development across front-end, back-end, test automation and mobile, ML Engineering, MLOps, LLMOps, Applied ML Sciences and ML Research, with a huge focus on GenAI capabilities. There is a huge emphasis on Large Language Models (LLMs) and Generative AI. Your contributions will be pivotal in delivering our new Generative AI-powered solutions for healthcare and enterprise customers. Qualifications Ph.D. Degree preferred. Experience having led multiple projects leveraging LLMs, GenAI and Prompt Engineering Exposure to real-world MLOps deploying models into production adding features to products Knowledge of working in a cloud environment 5+ Years of Experience Strong understanding of LLMs, GenAI, Prompt Engineering and Copilot Career Level - IC4 Responsibilities Responsibilities Strong expertise in Python programming and one of the Deep Learning frameworks (PyTorch, MXNet, TensorFlow, Keras) and understanding of LLMs, LLMOps and Generative AI - to be able to deliver per specifications; complete assignments without assistance by exercising judgment & appropriate actions Knowledge of Classification, Prediction, Recommender Systems, Time Series Forecasting, Anomaly Detection, Optimization, Graph ML, NLP. Hands-on develop ML models using the above techniques Ability to both use existing libraries (ML, Deep Learning, Re-inforcement Learning) as well as design algorithms ground-up; Able to prepare data pipelines and feature engineering pipelines to build robust models Combine ML Sciences depth, programming expertise and mathematical understanding of techniques to deliver state-of-the-art ML solutions for problem solving across Healthcare domain Drives selection of methods and techniques to drive solutions Demonstrate strong program management to be able to multi-task effectively Be able to mentor & lead junior data scientists effectively Contribute to peer reviews, team learning, meeting product objectives and develop best practices for the organization Strong research record preferred demonstrated, through publications Scientific thinking and ability to invent: Prior experience creating intellectual property through patents desirable Identify and investigate new technologies, prototype and test solutions for product features and design/validate patterns that deliver a compelling experience Take responsibility for technical problem solving to meet product objectives and develop best practices Ability to resolve complex business problems in creative and effective ways Strong experience in LLM Systems and LLMOps. Prior experience with Prompt Engineering and RAG systems

The Data Scientist is a technical role within the FMCG vertical, responsible for delivering high-quality end-to-end analytical solutions. Based in Hyderabad, this role collaborates with internal stakeholders and the wider team to transform client questions and issues into analytical solutions. How will you make an impact? Analytics Delivery: Deliver high-quality analytics, from data quality assessment to insights generation and visualization for FMCG projects Data Analysis & Insights: Transform transaction and customer-level datasets through comprehensive analytics processes Technical Implementation: Apply appropriate analytical methodologies and ensure quality in technical delivery Stakeholder Collaboration: Work effectively with team members and internal stakeholders to understand business requirements and deliver solutions Continuous Learning: Actively develop technical and commercial skills while building deep knowledge of Quantium's business and FMCG industry The superpowers you'll be bringing to the team: Technical Analytics Experience: 3+ years of experience in a highly technical analytics environment, carrying out data analytics or data science work Programming Proficiency: Strong coding experience in SQL and Python Business Understanding: Ability to translate business requirements into analytical solutions Industry Knowledge: Experience in FMCG/CPG or Retail industry (preferred) Collaboration Skills: Experience working with other Data Scientists and stakeholders in deadline-driven environments Problem-Solving: Strong analytical mindset with attention to detail Educational Background: Tertiary qualifications in engineering, mathematics, actuarial studies, statistics, physics, or a related discipline Analytics Knowledge: Strong foundation in data preparation, feature engineering, foundational analytics concepts, and model development

Practice Overview : Skill/Operating Group Technology Consulting Level Manager Location Gurgaon/Mumbai/ Bangalore Travel Percentage Expected Travel could be anywhere between 0-100% Why Technology Consulting The Technology Consulting business within Capability Network invents the future for clients by providing them with the right guidance, design thinking and innovative solutions for technological transformation. As technology rapidly evolves, it's more important than ever to have an innovation advisor who can create a new vision or put one into place"to solve the client's toughest business problems. Specialize in management or technology consulting to transform the worlds leading organizations by building innovative business solutions as their trusted advisor by: Helping Clients :Rethinking IT and Digital ecosystems and innovating to help clients keep pace with fast-changing, customer-driven environments. Enhancing your Skillset :Building expertise and innovating with leading-edge technologies such as Blockchain, Artificial Intelligence and Cloud. Transforming Businesses :Developing customized, next-generation products and services that help clients shift to new business models designed for todays connected"landscape of disruptive technologies Principal Duties And Resp o nsibilities: Working closely with our clients, consulting professionals design, architect, build and implement strategies, POC that can help enhance business performance. Develop specialized expertise "strategic, industry, functional, technical"in a diverse project environment that offers multiple opportunities for career growth." The opportunities to make a difference within exciting client initiatives are limitless in this ever-changing business landscape. Here are just a few of your day-to-day responsibilities. Identifying , Assessing and solving"complex business problems"for area of responsibility , where analysis of situations or data requires an in-depth evaluation of variable factors. Interact with client stakeholders to understand their AI problems, priority use-cases, define a problem statement, understand the scope of the engagement, and also drive projects to deliver value to the client Understand client's business and IT goals, vision and identify opportunities for reinvestment Through your expertise and experience, guide your team to suggest the right solutions to meet the needs of clients and help draw up practical implementation road maps that position them for long-term success Benchmark against global research benchmarks and leading industry peers to understand current & recommend AI solutions Conduct discovery workshops and design sessions to elicit AI opportunities & client pain areas. Technical SME to design & guide development of E nterprise wide AI architecture & strategy Managing multi-disciplinary teams to shape, sell, communicate and implement programs Contribute towards practice development initiatives like new offering development, people management etc Mentoring and People skill development Qualifications Qualifications: MBA Degree from Tier-1 College (Preferable) Bachelors Degree AI/ML/Cloud AI Certifications preferred Minimum of 10-15 years large scale consulting experience and managing teams in a consulting environment or at high tech companies Experience: We are looking for Advanced Analytics and AI Managers to join our growing team having experience with Machine learning and NLP applications . Operating across all stages of the innovation spectrum, with a remit to build the future in real-time. Experience in designing and building end-to-end AI Strategy & solutions using Cloud & Non-Cloud AI ML, NLP algo. Assessment: Works as part of multi-disciplinary teams and responsible for independently driving specific AI workstreams through collaboration with designers, other AI team members, platform & Data engineers, business subject matter experts and technology delivery teams to assess AI potential and develop use cases. Liaises effectively with global community and senior leadership to identify and drive value opportunities around AI, support investments in POCs, pilots and chargeable projects. Design: The Managers role on these projects centers around independently executing workstreams around the application of analytics, data science and advanced cognitive methods to derive insights & actions from data and develop POCs and appropriate high-level scalable solution designs . Strong expertise in designing AutoML , MLOps AI solutions using any of the Cloud services (AWS, GCP, Azure). Architecture: The nature of these projects change as ideas and concepts mature, ranging from research, proofs -of-concept and the art-of-the-possible to the delivery of real-world applications for our clients. Focus in this area is on the impact to clients technology landscape/ architecture and ensuring formulation of relevant guiding principles and platform components. Experti s e in designing Enterprise AI strategy, Responsible AI frameworks is preferred. Strong experience handling multiple end- to-end AI Lifecycle projects from Data preparation, Modeling, Build, Train & Deploy. Product/ Framework/ Tool evaluation: Collaborate with business experts for business understanding, working with other consultants and platform engineers for solutions and with technology teams for prototyping and client implementations. Evaluate existing products and frameworks available and develop options for proposed solutions. Have an understanding of the framework/ tools to engage the client in meaningful discussions and steer towards the right recommendation . Modeling: Strong SME knowledge in Data Preparation, Feature engineering, Feature selection, Training datasets, Algorithmic selection, Optimizing & Production deployment. Work as a technical SME to teams and client on advising right AI solutions. The Manager should have practical industry expertise . The areas of Financial Services, Retail, Telecommunications, Life Sciences and Resources are of interest but experience in equivalent domains is also welcomed. Consultants should understand the key technology trends in their domain and the related business implications.

Roles and Responsibilities Design, develop, and deploy machine learning models using various algorithms such as Bayesian statistics, frequentist statistics, optimization techniques, time series analysis, reinforcement learning, NLP, etc. Collaborate with stakeholders to understand business requirements and translate them into data science solutions. Develop high-quality code in Python (Pandas, NumPy, Matplotlib) or R (base packages) for building ML models. Ensure scalability and efficiency of deployed models by monitoring performance metrics like accuracy, precision, recall etc. Communicate complex technical insights effectively through reports and presentations. Desired Candidate Profile 4-8 years of experience in Data Science/Machine Learning Engineering with a strong background in finance/risk domain. Bachelor's degree in Any Specialization (B.Sc/B.Tech/B.E.). Proficiency in programming languages like Python/R; familiarity with cloud platforms like GCP/AWS/Azure; experience with big data tools like Spark/Hadoop. JD DETAILS- Data Scientist / Machine Learning Engineer - Neo soft client looking for candidates who are good in building ML Models for Financial/Risk verticals. make sure candidates have enough experience in building models. Job Title: Data Scientist / Machine Learning Engineer Experience: 4 Years Location: Bangalore (Lingarajapuram) Budget: 18 LPA What Youll Do You will work directly as part of AA CoE and be a part of analytics focused projects across statistics, optimization & simulations, machine learning and Big Data. Your role will involve design and implementation of advanced statistical analysis and machine learning algorithms to derive business insights and solve complex business problems. This includes gathering and analyzing information, formulating and testing hypotheses, and developing and communicating recommendations. You may also be responsible for presenting results to management and implementing recommendations with team members. You’ll have the opportunity to gain new skills and build on the strengths you bring to the company. Main task Design and implement machine-learning models to support the business’s numerous initiatives and programs with a view of achieving overall objectives and targets Successful documentation of reusable code Achieve personal technical development and learning goals Conduct knowledge sharing sessions internally within the CoE as well as externally in meetups, conferences etc. Participate in and help plan cultural initiatives for CoE Qualifications University degree in Computer Science, Engineering, Applied Mathematics or related fields and excellent academic record required; Master’s degree in above mentioned subjects preferred 4 years of technical experience in handling large datasets and applying advanced statistical and machine learning algorithms Hand-on experience in methodologies such as: Supervised and Unsupervised Learning, Feature Engineering, Bayesian Statistics, Frequentist Statistics, Optimization, Time Series, Graph/Network Theory, Reinforcement Learning, Deep Learning, Computer Vision, NLP, Interpretable AI, etc. Proficiency with at least one of the following languages: R, Python, SAS and experience of working with SQL/NoSQL databases Experience of working on platforms such as GCP, Dataiku, AWS, Azure, etc. Stakeholder management skills with ability to communicate and work with senior management effectively Skills to communicate complex ideas effectively