29 Reinforcement Learning Jobs

We are looking for "Data Scientist" with Minimum 4 years experience Contact- Yashra (95001 81847) Required Candidate profile Data Science, Agentic AI, LLM & RAC advanced machine learning (ML) and Agentic AI frameworks. generative AI, reinforcement learning, and multi-agent systems.

We are looking for a Junior Machine Learning Engineer with 4 to 6 years of experience to join our AI/ML team. The candidate will wok on reinforcement learning agents, end-to-end ML workflows, and MLOps practices to build, deploy, and monitor scalable AI solutions. Key Responsibilities: Develop and deploy ML models and RL agents (e.g., Q-learning, policy gradients). Preprocess data, perform feature engineering, and tune models. Operationalize models using Docker, CI/CD (GitHub Actions, Jenkins). Monitor model performance and system health in production. Collaborate with data scientists, engineers, and DevOps teams. Stay updated on trends in RL, AI, and MLOps. Required Skills: Bachelors/Masters in Computer Science or related field. Proficiency in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn). Hands-on experience with RL frameworks (OpenAI Gym, Stable Baselines). Familiarity with Docker, Git, CI/CD tools, and REST APIs. Understanding of ML lifecycle and cloud deployment (AWS/GCP/Azure). Preferred Skills: Experience with SageMaker, Vertex AI, or similar tools. Knowledge of deep learning, NLP, or microservices. Strong analytical and collaborative skills.

ob Title: AI Engineer. ey Responsibilities:. Architect, develop, and deploy advanced AI solutions, encompassing Machine Learning, Generative AI, NLP, and LLMs.. Remain abreast of the latest AI advancements, actively researching and integrating emerging trends and technologies such as LLMOps, Large Model Deployments, LLM Security, Vector Databases, etc.. Streamline data modeling processes to automate tasks, enhance data preparation, and facilitate data exploration to optimize business outcomes.. Collaborate closely with cross-functional teams, including business units, accounts teams, researchers, and engineers, to translate business requirements into actionable AI solutions.. Exhibit expertise in responsible AI practices, ensuring fairness, transparency, and interpretability in all models.. Identify and mitigate potential risks related to AI and LLM development and deployment, emphasizing data trust and security.. Contribute to the professional development of the AI team by mentoring engineers, fostering knowledge sharing, and promoting a culture of continuous learning.. This role is based in a lab environment and involves hands-on, fast-paced, and high-intensity work. The ideal candidate should be proactive, adaptable, and comfortable working in a dynamic and demanding setting.. ualifications:. Minimum of 2 years of hands-on experience in developing and deploying AI solutions, with a proven track record of success.. Master’s degree in Computer Science, Artificial Intelligence, or a related field (or equivalent experience).. Proficiency in Machine Learning, NLP, Generative AI, and LLMs, including their architectures, algorithms, and training methodologies.. Understanding of LLMOps principles, Prompt Engineering, In-Context Training, LangChain, and Reinforcement Learning.. Familiarity with best practices for large model deployment, monitoring, management, and scalability.. Experience with Azure Cloud services.. Strong communication, collaboration, and problem-solving abilities.. Commitment to ethical AI practices and security standards.. Proficiency in deep learning frameworks and languages such as Azure ML platform, Python, PyTorch, etc.. Hands-on experience with ML frameworks, libraries, and third-party ML models.. Expertise in building solutions using AI/ML/DL open-source tools and libraries.. Strong analytical and problem-solving skills.. Ability to write optimized and clear code, and address complex technical challenges effectively.. Self-motivated and fast learner, with a proactive approach to learning new technologies.. Proficiency in data analysis and troubleshooting skills.. Experience in building AI/ML/DL solutions for NLP/text applications, with familiarity in reinforcement learning being advantageous.. Minimum of 2 years of experience on AI/ML/DL projects, with specialization or certification in Artificial Intelligence being a plus.. Good knowledge of Azure AI/Cognitive Services tools.. Show more Show less

About NCR Atleos Overview Data is at the heart of our global financial network. In fact, the ability to consume, store, analyze and gain insight from data has become a key component of our competitive advantage. Our goal is to build and maintain a leading-edge data platform that provides highly available , consistent data of the highest quality for all users of the platform, including our customers, operations teams and data scientists. We focus on evolving our platform to deliver exponential scale to NCR Atleos , powering our future growth. Data & AI Engineers at NCR Atleos experience working at one of the largest and most recognized financial companies in the world, while being part of a software development team responsible for next generation technologies and solutions. Our engineers design and build large scale data storage, computation and distribution systems. They partner with data and AI experts to deliver high quality AI solutions and derived data to our consumers. We are looking for Data & AI Engineers who like to innovate and seek complex problems. We recognize that strength comes from diversity and will embrace your unique skills, curiosity, drive, and passion while giving you the opportunity to grow technically and as an individual. Engineers looking to work in the areas of orchestration, data modelling , data pipelines, APIs, storage, distribution, distributed computation, consumption and infrastructure are ideal candidates. Responsibilities As a Data Engineer, you will be joining a Data & AI team transforming our global financial network and improving the quality of our products and services we provide to our customers. and you will be responsible for designing, implementing, and maintaining data pipelines and systems to support the organizations data needs. Your role will involve collaborating with data scientists, analysts, and other stakeholders to ensure data accuracy, reliability, and accessibility. Key Responsibilities Data Pipeline DevelopmentDesign, build, and maintain scalable and efficient data pipelines to collect, process, and store structured and unstructured data from various sources. Data IntegrationIntegrate data from multiple sources such as databases, APIs, flat files, and streaming platforms into centralized data repositories. Data ModelingDevelop and optimize data models and schemas to support analytical and operational requirements. Implement data transformation and aggregation processes as needed. Data Quality AssuranceImplement data validation and quality assurance processes to ensure the accuracy, completeness, and consistency of data throughout its lifecycle. Performance Optimization Monitor and optimize data processing and storage systems for performance, reliability, and cost-effectiveness. Identify and resolve bottlenecks and inefficiencies in data pipelines and leverage Automation and AI to improve overall Operations. Infrastructure ManagementManage and configure cloud-based or on-premises infrastructure components such as databases, data warehouses, compute clusters, and data processing frameworks. CollaborationCollaborate with cross-functional teams including data scientists, analysts, software engineers, and business stakeholders to understand data requirements and deliver solutions that meet business objectives . Documentation and Best PracticesDocument data pipelines, systems architecture, and best practices for data engineering. Share knowledge and provide guidance to colleagues on data engineering principles and techniques. Continuous ImprovementStay updated with the latest technologies, tools, and trends in data engineering and recommend improvements to existing processes and systems. Qualifications and Skills: Bachelors degree or higher in Computer Science, Engineering, or a related field. Proven experience in data engineering or related roles, with a strong understanding of data processing concepts and technologies. Mastery of programming languages such as Python, Java, or Scala. Knowledge of database systems such as SQL, NoSQL, and data warehousing solutions. Knowledge of stream processing technologies such as Kafka or Apache Beam. Experience with distributed computing frameworks such as Apache Spark, Hadoop, or Apache Flink . Experience deploying pipelines in cloud platforms such as AWS, Azure, or Google Cloud Platform. Experience in implementing enterprise systems in production setting for AI, natural language processing. Exposure to self-supervised learning, transfer learning, and reinforcement learning is a plus . Have full stack experience to build the best fit solutions leveraging Large Language Models (LLMs) and Generative AI solutions with focus on privacy, security, fairness. Have good engineering skills to design the output from the AI with nodes and nested nodes in JSON or array, HTML formats for as-is consumption and display on the dashboards/portals. Strong problem-solving skills and attention to detail. Excellent communication and teamwork abilities. Experience with containerization and orchestration tools such as Docker and Kubernetes. Familiarity with data visualization tools such as Tableau or Power BI. EEO Statement NCR Atleos is an equal-opportunity employer. It is NCR Atleos policy to hire, train, promote, and pay associates based on their job-related qualifications, ability, and performance, without regard to race, color, creed, religion, national origin, citizenship status, sex, sexual orientation, gender identity/expression, pregnancy, marital status, age, mental or physical disability, genetic information, medical condition, military or veteran status, or any other factor protected by law. Statement to Third Party Agencies To ALL recruitment agenciesNCR Atleos only accepts resumes from agencies on the NCR Atleos preferred supplier list. Please do not forward resumes to our applicant tracking system, NCR Atleos employees, or any NCR Atleos facility. NCR Atleos is not responsible for any fees or charges associated with unsolicited resumes.

About the Team: ZF COE Team is effectively communicate complex technical concepts related to AI, ML, DL, and RL to both technical and non-technical audiences. This might involve presenting research findings at conferences or writing papers for academic journals. What you can look forward to as AI Research Scientist (m/f/d): Conduct cutting-edge research to identify and develop novel AI/ML methodologies, including Deep Learning (DL) and Reinforcement Learning (RL). Design and conduct experiments to test hypotheses, validate new approaches, and compare the effectiveness of different ML algorithms. Analyze data to uncover hidden patterns and relationships that can inform the development of new AI techniques. Stay at the forefront of the field by keeping abreast of the latest advancements in algorithms, tools, and theoretical frameworks. This might involve researching areas like interpretability of machine learning models or efficient training methods for deep neural networks. Prototype and explore the potential of advanced machine learning models, including deep learning architectures like convolutional neural networks (CNNs) or recurrent neural networks (RNNs). Contribute to the development of fundamental algorithms and frameworks that can be applied to various machine learning problems. This may involve improving existing algorithms or exploring entirely new approaches. Focus on theoretical aspects of model design, such as improving model efficiency, reducing bias, or achieving explainability in complex models. Document research methodologies, experimental procedures, and theoretical contributions for future reference and knowledge sharing within the research community. Contribute to the development of the research team's long-term research goals and strategies. Your profile as AI Research Scientist (m/f/d): Master's degree in Mathematics, Computer Science or other related technical fields. Phd is good to have. 8+ years of experience in research development, with a strong understanding of data structures and algorithms. 5+ years of experience building and deploying machine learning models in production. Proven experience with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn. Experience with distributed computing systems and large-scale data processing & Excellent communication and collaboration skills. Contribution to invention disclosure process & A strong publication record in top machine learning conferences or journals.

Role Summary As a Data Science Lead at Worley, you will collaborate with an established team to deliver high-impact data science and AI/ML projects for clients, while continuing to expand your own technical expertise. The role focuses particularly on working with unstructured data and involves designing scalable AI/ML solutions, staying on the leading edge of technology, and driving innovation across both internal and external stakeholders. Key Responsibilities Platform & Tool Development: Conceptualize, build, and manage AI/ML platforms with a focus on unstructured data. Evaluate and select the best AI/ML tools and frameworks in the industry. Leverage existing frameworks, standards, and patterns to create scalable architectural foundations. Solution Delivery & Ownership: Lead the development of cognitive solutions for both internal stakeholders and external customers. Conduct research in areas like Explainable AI, image segmentation, 3D object detection, and statistical methods. Ensure delivery of scalable, enterprise-grade applications and services. Strategic Insight & Innovation: Analyse global market trends (economic, social, cultural, technological) to identify AI/ML opportunities. Shape value propositions and recommendations using a global perspective. Evaluate algorithms, models, and emerging technologies to optimize organizational investment. Collaboration & Leadership: Guide and support data scientists and engineers in project execution involving large and complex datasets. Establish and oversee AI/ML lifecycle processes and best practices. Ensure collaboration across multi-disciplinary teams. Technical Skills & Experience AI/ML Expertise: Deep understanding of the full AI/ML project life cycle. Expert in deep learning and reinforcement learning. Experience with MLOps practices for effective model lifecycle management. Proficient in machine learning algorithms: k-NN, GBM, Naive Bayes, SVM, Neural Networks, Decision Forests. Tools & Frameworks: Hands-on experience with tools such as: Jupyter Hub, Zeppelin Notebook, Azure ML Studio TensorFlow, TensorFlow-Keras, PyTorch, SciKit-Learn, Spark MLlib Strong knowledge of CNN, R-CNN, LSTM, Encoder/Transformer architectures. Experience with deep learning models like Inception-ResNet and ResNeXt-50. Proven use of RNNs for text, speech, and generative models. Data Engineering & Storage: Familiarity with NoSQL databases (GraphX, Neo4J), document, columnar, and in-memory data models. Experience with ETL tools and platforms such as Talend, SAP BI Platform, SSIS, and MapReduce. Visualization & Reporting: Skilled in building KPI dashboards and storytelling visuals using tools like Tableau or Zoomdata. Preferred Qualifications Advanced degree in Data Science, Computer Science, AI/ML, or related fields. Demonstrated leadership in managing AI/ML projects and teams. Prior experience in consulting or energy/resources industries is a plus.

Role Summary As a Data Science Lead at Worley, you will collaborate with an established team to deliver high-impact data science and AI/ML projects for clients, while continuing to expand your own technical expertise. The role focuses particularly on working with unstructured data and involves designing scalable AI/ML solutions, staying on the leading edge of technology, and driving innovation across both internal and external stakeholders. Key Responsibilities Platform & Tool Development: Conceptualize, build, and manage AI/ML platforms with a focus on unstructured data. Evaluate and select the best AI/ML tools and frameworks in the industry. Leverage existing frameworks, standards, and patterns to create scalable architectural foundations. Solution Delivery & Ownership: Lead the development of cognitive solutions for both internal stakeholders and external customers. Conduct research in areas like Explainable AI, image segmentation, 3D object detection, and statistical methods. Ensure delivery of scalable, enterprise-grade applications and services. Strategic Insight & Innovation: Analyse global market trends (economic, social, cultural, technological) to identify AI/ML opportunities. Shape value propositions and recommendations using a global perspective. Evaluate algorithms, models, and emerging technologies to optimize organizational investment. Collaboration & Leadership: Guide and support data scientists and engineers in project execution involving large and complex datasets. Establish and oversee AI/ML lifecycle processes and best practices. Ensure collaboration across multi-disciplinary teams. Technical Skills & Experience AI/ML Expertise: Deep understanding of the full AI/ML project life cycle. Expert in deep learning and reinforcement learning. Experience with MLOps practices for effective model lifecycle management. Proficient in machine learning algorithms: k-NN, GBM, Naive Bayes, SVM, Neural Networks, Decision Forests. Tools & Frameworks: Hands-on experience with tools such as: Jupyter Hub, Zeppelin Notebook, Azure ML Studio TensorFlow, TensorFlow-Keras, PyTorch, SciKit-Learn, Spark MLlib Strong knowledge of CNN, R-CNN, LSTM, Encoder/Transformer architectures. Experience with deep learning models like Inception-ResNet and ResNeXt-50. Proven use of RNNs for text, speech, and generative models. Data Engineering & Storage: Familiarity with NoSQL databases (GraphX, Neo4J), document, columnar, and in-memory data models. Experience with ETL tools and platforms such as Talend, SAP BI Platform, SSIS, and MapReduce. Visualization & Reporting: Skilled in building KPI dashboards and storytelling visuals using tools like Tableau or Zoomdata. Preferred Qualifications Advanced degree in Data Science, Computer Science, AI/ML, or related fields. Demonstrated leadership in managing AI/ML projects and teams. Prior experience in consulting or energy/resources industries is a plus.

Role Summary As a Data Science Lead at Worley, you will collaborate with an established team to deliver high-impact data science and AI/ML projects for clients, while continuing to expand your own technical expertise. The role focuses particularly on working with unstructured data and involves designing scalable AI/ML solutions, staying on the leading edge of technology, and driving innovation across both internal and external stakeholders. Key Responsibilities Platform & Tool Development: Conceptualize, build, and manage AI/ML platforms with a focus on unstructured data. Evaluate and select the best AI/ML tools and frameworks in the industry. Leverage existing frameworks, standards, and patterns to create scalable architectural foundations. Solution Delivery & Ownership: Lead the development of cognitive solutions for both internal stakeholders and external customers. Conduct research in areas like Explainable AI, image segmentation, 3D object detection, and statistical methods. Ensure delivery of scalable, enterprise-grade applications and services. Strategic Insight & Innovation: Analyse global market trends (economic, social, cultural, technological) to identify AI/ML opportunities. Shape value propositions and recommendations using a global perspective. Evaluate algorithms, models, and emerging technologies to optimize organizational investment. Collaboration & Leadership: Guide and support data scientists and engineers in project execution involving large and complex datasets. Establish and oversee AI/ML lifecycle processes and best practices. Ensure collaboration across multi-disciplinary teams. Technical Skills & Experience AI/ML Expertise: Deep understanding of the full AI/ML project life cycle. Expert in deep learning and reinforcement learning. Experience with MLOps practices for effective model lifecycle management. Proficient in machine learning algorithms: k-NN, GBM, Naive Bayes, SVM, Neural Networks, Decision Forests. Tools & Frameworks: Hands-on experience with tools such as: Jupyter Hub, Zeppelin Notebook, Azure ML Studio TensorFlow, TensorFlow-Keras, PyTorch, SciKit-Learn, Spark MLlib Strong knowledge of CNN, R-CNN, LSTM, Encoder/Transformer architectures. Experience with deep learning models like Inception-ResNet and ResNeXt-50. Proven use of RNNs for text, speech, and generative models. Data Engineering & Storage: Familiarity with NoSQL databases (GraphX, Neo4J), document, columnar, and in-memory data models. Experience with ETL tools and platforms such as Talend, SAP BI Platform, SSIS, and MapReduce. Visualization & Reporting: Skilled in building KPI dashboards and storytelling visuals using tools like Tableau or Zoomdata. Preferred Qualifications Advanced degree in Data Science, Computer Science, AI/ML, or related fields. Demonstrated leadership in managing AI/ML projects and teams. Prior experience in consulting or energy/resources industries is a plus.

AI & Machine Learning Development: Develop, train, and fine-tune machine learning (ML) and deep learning (DL) models. Implement LLMs, NLP, reinforcement learning (RL), and computer vision (CV) models. Optimize retrieval-augmented generation (RAG) systems with vector databases (FAISS, Pinecone, Chroma). Work on multimodal AI systems integrating text, image, and audio processing. Agentic AI Systems Development: Build autonomous AI agents that can make decisions, learn from feedback, and interact with environments. Implement multi-agent frameworks using LangChain, CrewAI, AutoGen, BabyAGI, MetaGPT. Integrate AI agents with APIs, databases, and enterprise applications for real-world deployment. Software Engineering & MLOps: Design and deploy AI models using Docker, Kubernetes, and CI/CD pipelines. Implement MLOps workflows for continuous training, monitoring, and model retraining. Optimize AI solutions for cloud platforms (AWS, Azure, GCP) and edge computing. AI Governance & Security: Implement AI safety measures, including adversarial defense and bias mitigation. Ensure compliance with AI regulations (GDPR, HIPAA, SOC 2) and ethical AI principles. Secure AI agents against prompt injection, model poisoning, and adversarial attacks. Technical Skills: Strong programming skills in Python, Java, or R. Expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit-Learn). Experience with LLMs & NLP (Hugging Face, OpenAI API, BERT, GPT, Claude). Proficiency in multi-agent frameworks (LangChain, CrewAI, AutoGen). Knowledge of reinforcement learning (PPO, A3C, DDPG, SAC). Experience with vector databases (FAISS, Pinecone, Chroma) and knowledge graphs. Strong foundation in MLOps, cloud AI services (AWS, Azure AI, Google Vertex AI). Soft Skills: Strong analytical and problem-solving skills. Ability to work in a fast-paced, cross-functional team. Excellent communication and documentation skills. Preferred Qualifications: Master s. in Computer Science, AI, or Data Science. Certifications in AI/ML (AWS ML Specialist, Google ML Engineer, Microsoft AI Engineer). Experience with autonomous systems, robotics, or digital twins.

AI & Machine Learning Development: Develop, train, and fine-tune machine learning (ML) and deep learning (DL) models. Implement LLMs, NLP, reinforcement learning (RL), and computer vision (CV) models. Optimize retrieval-augmented generation (RAG) systems with vector databases (FAISS, Pinecone, Chroma). Work on multimodal AI systems integrating text, image, and audio processing. Agentic AI Systems Development: Build autonomous AI agents that can make decisions, learn from feedback, and interact with environments. Implement multi-agent frameworks using LangChain, CrewAI, AutoGen, BabyAGI, MetaGPT. Integrate AI agents with APIs, databases, and enterprise applications for real-world deployment. Software Engineering & MLOps: Design and deploy AI models using Docker, Kubernetes, and CI/CD pipelines. Implement MLOps workflows for continuous training, monitoring, and model retraining. Optimize AI solutions for cloud platforms (AWS, Azure, GCP) and edge computing. AI Governance & Security: Implement AI safety measures, including adversarial defense and bias mitigation. Ensure compliance with AI regulations (GDPR, HIPAA, SOC 2) and ethical AI principles. Secure AI agents against prompt injection, model poisoning, and adversarial attacks. Technical Skills: Strong programming skills in Python, Java, or R. Expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit-Learn). Experience with LLMs & NLP (Hugging Face, OpenAI API, BERT, GPT, Claude). Proficiency in multi-agent frameworks (LangChain, CrewAI, AutoGen). Knowledge of reinforcement learning (PPO, A3C, DDPG, SAC). Experience with vector databases (FAISS, Pinecone, Chroma) and knowledge graphs. Strong foundation in MLOps, cloud AI services (AWS, Azure AI, Google Vertex AI). Soft Skills: Strong analytical and problem-solving skills. Ability to work in a fast-paced, cross-functional team. Excellent communication and documentation skills. Preferred Qualifications: Master s. in Computer Science, AI, or Data Science. Certifications in AI/ML (AWS ML Specialist, Google ML Engineer, Microsoft AI Engineer). Experience with autonomous systems, robotics, or digital twins.

What You'll Do As an Optimization Scientist, you will design and deploy scalable optimization and reinforcement learning models to solve complex supply chain problems. You'll work on: Route Optimization:Solve VRP variants (Capacitated, Time Window, Multi-depot) using MILP, heuristics, and RL. Inventory Optimization:Develop multi-echelon inventory models using stochastic/dynamic programming and ADP. AI/OR Integration:Combine ML forecasts, OR models, and RL agents for end-to-end decision automation. Simulation & Deployment:Build simulation environments and deploy models in real-world systems. What We're Looking For Degree in Operations Research, Industrial Engineering, Applied Math, Computer Science, or related fields. 1+ years of experience in solving OR problems (LP/MILP, heuristics, metaheuristics). Hands-on experience with RL algorithms (PPO, DQN, A3C) and toolkits (OpenAI Gym, RLlib, Stable-Baselines3). Strong Python skills with libraries like Gurobi, Pyomo, NumPy, Pandas, TensorFlow/PyTorch. Why Join Us Work on real-world, high-impact problems in supply chain and logistics. Collaborate with a world-class team of scientists and engineers. Flexible, innovation-driven culture with opportunities for growth.

Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or specialized utility programs that launch cutting-edge, world class products that meet and exceed customer needs. Qualcomm Software Engineers collaborate with systems, hardware, architecture, test engineers, and other teams to design system-level software solutions and obtain information on performance requirements and interfaces. Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience. 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc. Location - Hyderabad Experience - 3-8 Years We are seeking an experienced Machine Learning Engineers specializing in Generative AI to join our core AI team. The ideal candidate will be responsible for designing, developing, and deploying cutting-edge generative AI solutions, with a focus on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Intelligent agent systems. Key Responsibilities: Design and implement RAG-based solutions to enhance LLM capabilities with external knowledge sources Develop and optimize LLM fine-tuning strategies for specific use cases and domain adaptation Create robust evaluation frameworks for measuring and improving model performance Build and maintain agentic workflows for autonomous AI systems Collaborate with cross-functional teams to identify opportunities and implement AI solutions Required Qualifications: Bachelor's or Master's degree in Computer Science, or related technical field 3+ years of experience in Machine Learning/AI engineering Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow) Practical experience with LLM deployments and fine-tuning Experience with vector databases and embedding models Familiarity with modern AI/ML infrastructure and cloud platforms (AWS, GCP, Azure) Strong understanding of RAG architectures and implementation Preferred Qualifications: Experience with popular LLM frameworks (Langchain, LlamaIndex, Transformers) Knowledge of prompt engineering and chain-of-thought techniques Experience with containerization and microservices architecture Background in NLP and deep learning Background in Reinforcement Learning Contributions to open-source AI projects Experience with ML ops and model deployment pipelines Skills and Competencies: Strong problem-solving and analytical skills Excellent communication and collaboration abilities Experience with agile development methodologies Ability to balance multiple projects and priorities Strong focus on code quality and best practices Understanding of AI ethics and responsible AI development

As a Senior Data Scientist, you will apply your expertise in statistics, machine learning, and data analysis to extract valuable insights from structured and unstructured data. You will work closely with cross-functional teams to develop predictive models, improve business processes, and contribute to data-driven decision-making across the organization. Required Skills (Must have) Tech: Advanced programming knowledge in Python and SQL. Advanced knowledge in Probability and Statistics, including hypothesis testing. Advanced knowledge in Practical Machine Learning and awareness of the key-pitfalls in the practice of machine learning and approaches to addressing them. Advanced knowledge of data visualization technologies like Tableau, and PowerBI, and comfortable using relevant libraries in Python like seaborn and matplotlib. Experienced in modern development tools and writing code collaboratively. Intermediate knowledge of Cloud technologies and experience in developing data science solutions in one or more cloud platforms. Experienced in modern development tools, writing code collaboratively and developing solutions on cloud platforms. Non Tech : Ability to recognize and pursue pragmatic alternatives vis--vis a perfect solution, balancing priorities of time with potential business impact. Plan projects, break them down across individual data scientists in the team, track their performance and manage risks. Ability to storyboard an entire presentation to a non-technical audience. Ability to work independently to develop data science solutions, while also being able to work as part of a team to communicate findings and collaborate on solutions. Strong written skills. This is required for submitting technical papers, whitepapers, and developing project documentations. Technical leadership and mentorship to the community of data scientists in the organization. Required Skills (Good to have) Tech: Advanced knowledge in one or more areas besides Machine Learning – Operations Research, Natural Language Processing, Deep learning and its applications, Time Series forecasting at scale. Reinforcement Learning, Graph Machine Learning, Explainable Machine learning. Advanced understanding of Cloud technologies and experience of deploying applications on cloud. Non Tech: Ability to solution critical business problems into its component parts and match each such part with an appropriate technical approach. Roles and Responsibilities As Senior Data Scientist, you will be responsible for a wide range of engagements listed below: Formulates complex problems into hypotheses and proofs of concept for testing. Socializes this with the rest of the team and guides them to deliver on it. Applies business acumen in analyses to extract meaningful and actionable information. Communicates complex ideas and insights effectively to stakeholders with various levels of technical experience. Leverages various analytical techniques, appropriate to solving the business problem at hand. Performs research for solutions and solves problems efficiently to overcome data analytics challenges. Engages in the collection, integration, analysis, and presentation of data for various business contexts Understands good software development practices (versioning, peer reviews, refactoring, and pair programming), adapts them to the needs of the team and sets an example for others by following them. Creates and maintains technical documentation of the scientific experimentations performed, preferably in the CRISP-DM framework or like. Keeps up with the latest trends, technologies, and best practices in the field of Data Science and Engineering. Shares this knowledge with the rest of the data science team. Does peer reviews of codes and approaches of fellow members of the data science team. Provides mentorship to junior data scientists in the team. Looks for improvements in data science delivery processes, actively seeks buy-in on the improvements from peers and managers, implements them in the team and monitors their adoption. 4 to 6 years experience is mandatory

We are seeking a highly skilled and innovative AI Data Engineer to join our Development team. In this role, you will design, develop, and deploy AI systems that can generate content, reason autonomously, and act as intelligent agents in dynamic environments. Key Responsibilities • Design and implement generative AI models (e.g., LLMs, diffusion models) for text, image, audio, or multimodal content generation. • Develop agentic AI systems capable of autonomous decision-making, planning, and tool use in complex environments. • Integrate AI agents with APIs, databases, and external tools to enable real-world task execution. • Fine-tune foundation models for domain-specific applications using techniques like RLHF, prompt engineering, and retrieval-augmented generation (RAG). • Collaborate with cross-functional teams including product, design, and engineering to bring AI-powered features to production. • Conduct research and stay up to date with the latest advancements in generative and agentic AI. • Ensure ethical, safe, and responsible AI development practices. Required Qualifications • Bachelors or Masters degree in Computer Science, AI, Machine Learning, or a related field. • 3+ years of experience in machine learning, with a focus on generative models or autonomous agents. • Proficiency in Python and ML frameworks such as PyTorch • Experience with LLMs (e.g., GPT, Claude, LLaMA, Cortex), transformers, and diffusion models. • Familiarity with agent frameworks (e.g., LangChain, AutoGPT, ReAct, OpenAgents). • Experience with AWS and Snowflake services • Prior Healthcare experience • Strong understanding of reinforcement learning, planning algorithms, and multi-agent systems. • Excellent problem-solving and communication skills. Shift Timings - 12 PM - 9 PM Office location -Bangalore/ Gurgaon ( Carelon offc locations )

Key Responsibilities: Annotate and evaluate AI-generated research content in the field of AI, machine learning, and related domains Design research prompts and assess AI responses for clarity, relevance, and scientific accuracy in AI and machine learning concepts Provide detailed feedback to enhance the AI's research quality and its ability to produce valuable, high-impact insights Collaborate with AI teams to improve the integration of research findings into practical AI applications and systems Develop novel algorithms and models for AI-driven applications across various domains Collaborate with cross-functional teams to integrate research outcomes into production-level systems and products Required Qualifications: Strong background in machine learning, deep learning, reinforcement learning, or natural language processing Proven track record of original research, including publications in leading AI conferences or journals Expertise in programming languages such as Python, C++, or similar, and knowledge of machine learning frameworks (e g, TensorFlow, PyTorch) Ability to think critically and creatively to address complex AI challenges Excellent problem-solving skills, strong communication skills, and the ability to collaborate effectively in a team setting Location: Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

Principal – AI/ML Engineer (Agents and Agentic Design) What you will do Let’s do this. Let’s change the world. We are seeking a Principal AI/ML Engineer (Agents and Agentic Design) to drive innovation in AI/ML and agent-based system design at Amgen. This role is integral to advancing the organization's AI strategy by developing intelligent, scalable, and secure multi-agent systems. The Principal AI/ML Engineer will be responsible for leading technical innovation, mentoring AI/ML teams, and integrating agent-based solutions into enterprise platforms. The key aspects of this role involve: Prior hands-on experience designing and implementing sophisticated AI/ML systems with multiple interacting agents. Leadership experience in guiding AI/ML teams and setting strategic direction for agent-based frameworks. Delivering AI/ML solutions that enhance efficiency, scalability, and business value across enterprise-level platforms. Roles & Responsibilities: AI/ML Thought Leadership & Mentorship Mentor and provide thought leadership for AI/ML engineers and data scientists, enabling continuous technical growth in agentic design, reinforcement learning, and AI standard methodologies. Agent-Based System Development Design, implement, and optimize multi-agent AI/ML systems that enhance automation, decision-making, and system efficiency. Strategic Framework Development Define and set the direction for AI/ML frameworks that enable scalable and robust agentic solutions. Enterprise-Level Integration Work closely with multi-functional teams to integrate agent-based solutions into Amgen’s enterprise platforms, aligning AI strategies with business objectives. Technical Innovation & Research Stay at the forefront of AI/ML advancements, exploring and implementing new methodologies such as reinforcement learning, active learning, and RLHF to drive continuous improvement. Cross-Functional Collaboration Partner with leadership, product teams, and other collaborators to identify AI opportunities, streamline implementations, and align AI/ML strategies with company goals. Quality & Performance Assurance Ensure that AI solutions meet enterprise-scale performance, security, and reliability standards, while maintaining detailed documentation for long-term scalability. What we expect of you We are all different, yet we all use our unique contributions to serve patients. Basic Qualifications: Master’s degree and 8 to 10 years of AI, machine learning, and/or data science experience OR Bachelor’s degree and 10 to 14years of AI, machine learning, and/or data science experience OR Diploma and 14 to 18 years ofAI, machine learning, and/or data science experience Proven expertise in designing and implementing AI/ML systems with multiple interacting agents. Demonstrated experience in reinforcement learning, active learning, and RLHF methodologies. Strong background in authoring and managing highly complex technical documentation at an enterprise level. Extensive experience in AI/ML system design, with a focus on multi-agent interactions and agentic design. Deep familiarity with agent-based modeling tools and frameworks. Proficiency in reinforcement learning, active learning, and RLHF methodologies. Strong background in developing scalable AI architectures, ensuring robustness, efficiency, and security. Experience with enterprise-scale AI/ML deployments and integrating agent-based solutions into business processes. Knowledge of cloud-based AI/ML frameworks and tools for large-scale model training and deployment. Preferred Qualifications: Familiarity with data security and privacy regulations as they pertain to AI/ML applications. Experience in writing and managing complex technical documentation at an enterprise level. Strong project management skills with a track record of delivering AI-driven initiatives on time and within scope. Soft Skills: Leadership & Vision: Ability to inspire and guide teams toward achieving AI/ML innovation and excellence. Strategic Thinking: Capable of developing and implementing long-term AI strategies that align with business needs. Collaboration: Proven experience working across different teams and subject areas to drive AI/ML integration. Communication: Ability to convey complex AI/ML concepts to both technical and non-technical collaborators. Adaptability: A forward-thinking approach that embraces emerging AI technologies and evolving industry trends. What you can expect of us As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we’ll support your journey every step of the way. In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards. Apply now for a career that defies imagination Objects in your future are closer than they appear. Join us. careers.amgen.com As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease. Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Tech Lead - Data Scientist Chennai - Guindy, India Information Technology 17100 Overview Seeking an experienced Tech Lead Data Scientist with 7 to 9 years of industry experience, including a minimum of 34 years in Machine Learning, NLP, and LLM-Ops, to support the development and deployment of scalable AI solutions. The ideal candidate should have hands-on expertise in Python, AWS, and ML-Ops pipelines, with experience in building RAG systems and working with large language models. This role involves developing production-ready ML systems, automating model workflows, and contributing to high-impact, cloud-based AI initiatives within an agile environment. Responsibilities Lead the design, development, and optimization of end-to-end ML and NLP systems in production environments. Collaborate on the deployment of machine learning models using ML-Ops/LLM-Ops pipelines on AWS or other cloud platforms. Develop Retrieval-Augmented Generation (RAG) systems for complex NLP tasks, ensuring scalability and low-latency processing. Architect solutions for the integration and scaling of ML models in distributed environments using cloud technologies such as AWS, Azure, or Google Cloud . Maintain and enhance large-scale machine learning models in production, ensuring high availability and performance. Drive the automation of model retraining, monitoring, and validation workflows within ML-Ops pipelines. Work with cross-functional teams to create optimized, robust, and scalable machine learning solutions that directly impact the business. Requirements Technical Requirements 4+ years of hands-on experience in Machine Learning (ML), Natural Language Processing (NLP), and working with Large Language Models (LLMs) . Proficiency in Python for ML development and integration into production systems. Strong experience in deploying ML models using AWS (or other cloud platforms) with a focus on ML-Ops practices for continuous integration, deployment, and monitoring. Experience in LLM-Ops and the operationalization of large language models in production environments. Proficiency in developing RAGs (Retrieval-Augmented Generation) systems or similar knowledge-enhanced retrieval frameworks. Strong foundation in software development best practices for AI/ML, including testing, optimization, and performance tuning. Familiarity with cloud services and tools like S3, Lambda, Kubernetes , and Docker for scalable deployments. Preferred Qualifications Hands-on experience with Computer Vision or Reinforcement Learning techniques is a plus. Familiarity with database management using Oracle or PL/SQL . Experience with Agile development processes and tools such as Jira and Confluence . Ability to manage and prioritize multiple projects in a fast-paced, agile environment with a focus on high-quality delivery. Must-Have Qualifications Bachelor's or Master's degree in computer science, Data Science, or related fields from a reputed institution (IIT, DCE, NIT, or equivalent). Proven experience in the full ML lifecycle , from research to production, with a focus on performance, scalability, and robustness. Strong analytical and problem-solving skills, with a creative and entrepreneurial mindset.

Senior AI/ML Engineer Chennai, India Information Technology 17102 Overview Seeking an experienced Senior AI/ML Engineer with 3 to 5 years of industry experience, including a minimum of 23 years in Machine Learning, NLP, and LLM-Ops, to support the development and deployment of scalable AI solutions. The ideal candidate should have hands-on expertise in Python, AWS, and ML-Ops pipelines, with experience in building RAG systems and working with large language models. This role involves developing production-ready ML systems, automating model workflows, and contributing to high-impact, cloud-based AI initiatives within an agile environment. Responsibilities Design, develop, and optimize end-to-end machine learning and NLP solutions for production-grade systems. Collaborate on deploying ML models through ML-Ops/LLM-Ops pipelines on AWS or other cloud platforms. Build and implement Retrieval-Augmented Generation (RAG) systems to solve complex NLP tasks, ensuring scalability and low-latency performance. Contribute to the integration and scaling of ML models in distributed environments using cloud technologies like AWS, Azure, or GCP. Maintain and fine-tune large-scale machine learning models in production, ensuring reliability and performance. Support automation of model retraining, monitoring, and validation workflows within ML-Ops pipelines. Work closely with cross-functional teams to deliver robust, efficient, and business-impacting AI/ML solutions. Requirements Technical Requirements 2+ years of hands-on experience in Machine Learning (ML), Natural Language Processing (NLP), and working with Large Language Models (LLMs) . Proficiency in Python for ML development and integration into production systems. Strong experience in deploying ML models using AWS (or other cloud platforms) with a focus on ML-Ops practices for continuous integration, deployment, and monitoring. Experience in LLM-Ops and the operationalization of large language models in production environments. Proficiency in developing RAGs (Retrieval-Augmented Generation) systems or similar knowledge-enhanced retrieval frameworks. Strong foundation in software development best practices for AI/ML, including testing, optimization, and performance tuning. Familiarity with cloud services and tools like S3, Lambda, Kubernetes , and Docker for scalable deployments. Preferred Qualifications Hands-on experience with Computer Vision or Reinforcement Learning techniques is a plus. Familiarity with database management using Oracle or PL/SQL . Experience with Agile development processes and tools such as Jira and Confluence . Ability to manage and prioritize multiple projects in a fast-paced, agile environment with a focus on high-quality delivery. Must-Have Qualifications Bachelor's or Master's degree in computer science, Data Science, or related fields from a reputed institution (IIT, DCE, NIT, or equivalent). Proven experience in the full ML lifecycle , from research to production, with a focus on performance, scalability, and robustness. Strong analytical and problem-solving skills, with a creative and entrepreneurial mindset.

Lead AI/ML Engineer Bangalore, India Information Technology 17101 Overview Seeking an experienced Lead AI/ML Engineer with 5 to 7 years of industry experience, including a minimum of 34 years in Machine Learning, NLP, and LLM-Ops, to support the development and deployment of scalable AI solutions. The ideal candidate should have hands-on expertise in Python, AWS, and ML-Ops pipelines, with experience in building RAG systems and working with large language models. This role involves developing production-ready ML systems, automating model workflows, and contributing to high-impact, cloud-based AI initiatives within an agile environment. Responsibilities Key Responsibilities Lead the design, development, and optimization of end-to-end ML and NLP systems in production environments. Collaborate on the deployment of machine learning models using ML-Ops/LLM-Ops pipelines on AWS or other cloud platforms. Develop Retrieval-Augmented Generation (RAG) systems for complex NLP tasks, ensuring scalability and low-latency processing. Architect solutions for the integration and scaling of ML models in distributed environments using cloud technologies such as AWS, Azure, or Google Cloud . Maintain and enhance large-scale machine learning models in production, ensuring high availability and performance. Drive the automation of model retraining, monitoring, and validation workflows within ML-Ops pipelines. Work with cross-functional teams to create optimized, robust, and scalable machine learning solutions that directly impact the business. Requirements Technical Requirements 3+ years of hands-on experience in Machine Learning (ML), Natural Language Processing (NLP), and working with Large Language Models (LLMs) . Proficiency in Python for ML development and integration into production systems. Strong experience in deploying ML models using AWS (or other cloud platforms) with a focus on ML-Ops practices for continuous integration, deployment, and monitoring. Experience in LLM-Ops and the operationalization of large language models in production environments. Proficiency in developing RAGs (Retrieval-Augmented Generation) systems or similar knowledge-enhanced retrieval frameworks. Strong foundation in software development best practices for AI/ML, including testing, optimization, and performance tuning. Familiarity with cloud services and tools like S3, Lambda, Kubernetes , and Docker for scalable deployments. Preferred Qualifications Hands-on experience with Computer Vision or Reinforcement Learning techniques is a plus. Familiarity with database management using Oracle or PL/SQL . Experience with Agile development processes and tools such as Jira and Confluence . Ability to manage and prioritize multiple projects in a fast-paced, agile environment with a focus on high-quality delivery. Must-Have Qualifications Bachelor's or Master's degree in computer science, Data Science, or related fields from a reputed institution (IIT, DCE, NIT, or equivalent). Proven experience in the full ML lifecycle , from research to production, with a focus on performance, scalability, and robustness. Strong analytical and problem-solving skills, with a creative and entrepreneurial mindset.

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. Primary Responsibilities Develop and deploy innovative AI solutions to various business problems. Should be able to apply some of the most cutting-edge AI technologies Research and evaluate new data sources, AI technology trends and methodologies to enhance Organization level data science capabilities and solutions Perform data analysis, pre-processing and feature engineering required to ensure quality and reliability of the AI models and optimize them for performance and robustness Analyzes and investigates Provides explanations and interpretations within area of expertise Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications Bachelor’s degree or higher in computer science engineering with a focus on language processing. Overall 4+ years of experience in AI ML roles Experience implementing multiple machine learning and AI techniques such as supervised, unsupervised, reinforcement learning, Deep learning, NLP Understanding of Both Opensource and Open AI LLMs and RAG architecture Proficiency in libraries such as Hugging face and OpenAI API Proficiency with cloud development environments such as Azure Proficiency with experience in ML and NLP R&D with demonstrable impact Proven excellent analytical and problem-solving skills, including the ability to disaggregate issues, identify root causes and recommend solutions Proven good grasp of using LLMs, Deploying LLMs At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes — an enterprise priority reflected in our mission.

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by diversity and inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together. We are seeking a dynamic and skilled AIML architect who is passionate about solving real world problems in the healthcare domain using cutting edge capabilities and emerging technologies. As an AI solution architect, you will be responsible for developing AI business case, solution design and as needed prototypes. You will follow advancements in the state-of-the-art methods that are relevant to the particular use case and provide recommendations for model development and experimentation. Primary Responsibilities Develop and implement AI/ML strategies, vision, and guidelines in collaboration with business and IT stakeholders Design innovative AI solutions to various business problems, utilizing cutting-edge AI technologies Work on transformational AI and automation initiatives to support business priorities Research and evaluate new data sources, AI technology trends, and methodologies to enhance organizational data science capabilities and solutions Educate the team on AI technologies, best practices, and responsible use of AI Collaborate with cross-functional teams to understand business requirements and translate them into architecture solutions Ensure the scalability, reliability, and efficiency of AI/ML solutions in production environments Stay updated with the latest advancements in AI/ML techniques and tools and identify opportunities to enhance existing solutions Document and communicate findings, methodologies, and insights to technical and non-technical stakeholders Utilize frameworks such as Scikit Learn, TensorFlow, PyTorch, Vertex AI, and Azure AI Studio Navigate MLRB processes in partnership with others for new AI use cases and deployments Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications Bachelor’s or Master’s degree in computer science, Data Science, Statistics, or a related field 3+ years of experience in Data Science, AI/ML, or a similar role Experience implementing multiple machine learning techniques such as supervised, unsupervised, reinforcement learning, Deep learning, NLP Experience with the full life cycle of AI/ML projects, including EDA, model development, tuning, and drift analysis Hands-on experience in delivering production-grade AI/ML projects Solid technical writing skills and must have published research papers in leading academic journals on topics related to Artificial Intelligence & Machine Learning Proven excellent analytical and problem-solving skills, including the ability to disaggregate issues, identify root causes and recommend solutions Proven sound understanding of common NLP tasks such as text classification, entity recognition, entity extraction, and question answering Proficiency in frameworks such as Scikit Learn, TensorFlow, and PyTorch Solid understanding of mathematical and statistical concepts Proven excellent problem-solving and analytical thinking skills Solid communication and collaboration skills to work effectively in a team environment Preferred Qualifications Familiarity with the US Healthcare domain Experience in AIML R&D with demonstrable impact At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes — an enterprise priority reflected in our mission.

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. Primary Responsibilities Develop and deploy innovative AI solutions to various business problems. Should be able to apply some of the most cutting-edge AI technologies Research and evaluate new data sources, AI technology trends and methodologies to enhance Organization level data science capabilities and solutions Perform data analysis, pre-processing and feature engineering required to ensure quality and reliability of the AI models and optimize them for performance and robustness Analyzes and investigates Provides explanations and interpretations within area of expertise Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications Bachelor’s degree or higher in computer science engineering with a focus on language processing. Overall 4+ years of experience in AI ML roles Experience implementing multiple machine learning and AI techniques such as supervised, unsupervised, reinforcement learning, Deep learning, NLP Understanding of Both Opensource and Open AI LLMs and RAG architecture Proficiency in libraries such as Hugging face and OpenAI API Proficiency with cloud development environments such as Azure Proficiency with experience in ML and NLP R&D with demonstrable impact Proven excellent analytical and problem-solving skills, including the ability to disaggregate issues, identify root causes and recommend solutions Proven good grasp of using LLMs, Deploying LLMs At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes — an enterprise priority reflected in our mission.

Job Description: We are seeking a highly motivated and skilled AI Developer to join our dynamic team. The ideal candidate should have hands-on experience in designing, developing, and deploying AI and machine learning models to solve real-world problems. You will work closely with data scientists, software engineers, and product teams to build intelligent applications. Key Responsibilities: Design and develop AI/ML models based on business requirements Preprocess and analyze structured and unstructured data Implement Deep Learning and NLP algorithms using frameworks like TensorFlow, PyTorch, and Scikit-learn Collaborate with software engineers to integrate models into production environments Build and optimize pipelines for data ingestion, model training, and inference Monitor model performance and retrain as needed Research and implement state-of-the-art algorithms Create dashboards or front-end demos using Streamlit or similar tools (optional) Key Skills Required: Programming: Python (Must), R (Optional), Java (Good to have) AI/ML: TensorFlow, PyTorch, Keras, Scikit-learn Data Science: Pandas, NumPy, Matplotlib, Seaborn NLP: Hugging Face Transformers, NLTK, SpaCy Computer Vision: OpenCV, YOLO, CNNs Model Deployment: Flask, FastAPI, Docker, AWS/Azure/GCP Databases: SQL, MongoDB, Firebase (optional) Version Control: Git, GitHub Preferred Qualifications: Bachelors or Master’s degree in Computer Science, AI, Data Science, or related field Strong mathematical foundation in statistics, linear algebra, and probability Excellent problem-solving skills and attention to detail Strong communication and teamwork skills Why Join Us? Work on cutting-edge AI solutions Collaborative and inclusive work environment Opportunity to grow in a fast-paced tech-driven organization Exposure to real-world enterprise and consumer AI applications

Duration: 8Months Work Type: Onsite Position Description: Looking for qualified Data Scientists who can develop scalable solutions to complex real-world problems using Machine Learning, Big Data, Statistics, and Optimization. Potential candidates should have hands-on experience in applying first principles methods, machine learning, data mining, and text mining techniques to build analytics prototypes that work on massive datasets. Candidates should have experience in manipulating both structured and unstructured data in various formats, sizes, and storage-mechanisms. Candidates should have excellent problem-solving skills with an inquisitive mind to challenge existing practices. Candidates should have exposure to multiple programming languages and analytical tools and be flexible to using the requisite tools/languages for the problem at-hand. Skills Required: Machine Learning, GenAI, LLM Skills Preferred: Python, Google Cloud Platform, Big Query Experience Required: 3+ years of hands-on experience in using machine learning/text mining tools and techniques such as Clustering/classification/decision trees, Random forests, Support vector machines, Deep Learning, Neural networks, Reinforcement learning, and other numerical algorithms Experience Preferred: 3+ years of experience in at least one of the following languages: Python, R, MATLAB, SAS Experience with GoogleCloud Platform (GCP) including VertexAI, BigQuery, DBT, NoSQL database and Hadoop Ecosystem Education Required: Bachelor's Degree

Machine Learning Subject Matter Expert (SME) Course Creator We are seeking a Machine Learning Subject Matter Expert (SME) – Course Creator to design and develop engaging, high-quality machine learning (ML) courses aligned with our instructional design framework. The ideal candidate will collaborate with instructional designers, content developers, and multimedia teams to create learner-focused courses that cater to a global audience. Key Responsibilities: Design and structure machine learning courses for us, ensuring alignment with industry trends and best practices. Develop course modules, learning objectives, assessments, quizzes, and capstone projects to enhance learning outcomes. Create engaging content using Jupyter Notebooks, Python, TensorFlow, PyTorch, Scikit-learn, and other ML tools. Integrate real-world case studies, hands-on coding exercises, and interactive learning experiences. Work closely with instructional designers to implement pedagogically sound teaching methodologies (e.g., project-based learning, microlearning). Develop video scripts, slide decks, and supplementary materials for the hosted courses. Ensure content is accessible, interactive, and aligned with our Learning Experience Platform (LXP). Stay up to date with emerging ML trends, AI advancements, and our course creation guidelines. Required Skills & Qualifications: Master’s or Ph.D. in Machine Learning, Data Science, Computer Science, or a related field. 5+ years of experience in ML research, development, or teaching. Expertise in Python, TensorFlow, PyTorch, Scikit-learn, and other ML libraries. Experience in building and deploying ML models in real-world applications. Strong understanding of supervised, unsupervised, deep learning, and reinforcement learning techniques. Familiarity with cloud-based ML platforms (AWS, GCP, Azure ML). Prior experience in creating online courses, MOOCs, or technical content for learning platforms like Coursera, Udacity, or edX. Ability to explain complex ML concepts in a simple, engaging, and interactive manner. Strong technical writing and communication skills. Preferred Qualifications: Experience working with LMS platforms and course creation tools (Articulate, Camtasia, Jupyter Notebooks). Knowledge of AI ethics, explainable AI (XAI), and responsible AI development. Previous experience as a course instructor, mentor, or content contributor.