Senior AI/ML Engineer - Python,LLM's, MachineLearning, DeepLearning, BigDataAnalytics

Requisition Number: 2390917
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:

• Lead the end-to-end design and delivery of AI/ML solutions, from business problem framing, data preparation, experimentation, and model development to production deployment and support
• Develop and apply machine learning, deep learning, natural language processing, computer vision, and generative AI techniques based on the needs of the use case
• Build, fine-tune, evaluate, optimize, and integrate predictive models, large language models, retrieval-augmented generation (RAG) solutions, and AI agents
• Design secure, scalable, and well-documented REST APIs and microservices using Python frameworks such as FastAPI or Flask to expose AI capabilities to enterprise applications
• Design and develop responsive web-based user interfaces using modern front-end frameworks such as React or Angular; integrate UI workflows with AI services and APIs
• Establish model evaluation approaches using appropriate metrics such as precision, recall, F1 score, ROC-AUC, latency, throughput, groundedness, relevance, and quality measures based on the solution type
• Implement MLOps and LLMOps practices for experiment tracking, model versioning, automated testing, CI/CD, deployment, monitoring, drift detection, observability, and controlled rollback
• Create reusable AI components, reference architectures, coding standards, engineering guardrails, and technical documentation to accelerate delivery across the team
• Lead architecture and design discussions; select fit-for-purpose technologies and make informed trade-offs across model quality, scalability, security, maintainability, performance, and cost
• Partner with Product Management, business stakeholders, data scientists, data engineers, architects, security teams, and platform teams for backlog refinement, planning, estimation, and delivery
• Lead and mentor AI/ML and full-stack engineers through technical direction, code reviews, design reviews, pair programming, troubleshooting, and engineering best practices
• Ensure responsible AI practices, human oversight, privacy, security, explainability, bias assessment, auditability, and compliance requirements are incorporated throughout the solution lifecycle
• Investigate complex production issues across data pipelines, models, APIs, UI, cloud infrastructure, and integrations; drive root-cause analysis and sustainable corrective actions
• Communicate technical concepts, solution risks, model limitations, outcomes, and recommendations clearly to engineering teams, business partners, and leadership
• Work effectively and demonstrate ownership, collaboration, sound judgment, adaptability, and a delivery-focused mindset
• Comply with all applicable Company policies, procedures, and business directives, changes including those relating to work location, team assignments, work schedules, and flexible work arrangements

Required Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related technical discipline
• 8+ years of overall software engineering experience, including significant hands-on experience delivering AI/ML solutions and providing technical leadership to engineering teams
• Hands-on experience with deep learning architectures and frameworks such as PyTorch or TensorFlow, including neural networks, transformers, embeddings, and model optimization techniques
• Hands-on Python development experience and proficiency with AI/ML libraries such as scikit-learn, pandas, NumPy or equivalent technologies
• Experience developing generative AI solutions using large language models, prompt engineering, RAG, vector databases, semantic search, orchestration frameworks such as Lang Chain or Semantic Kernel, and model evaluation techniques
• Experience designing secure REST APIs and production microservices using FastAPI, Flask, or equivalent frameworks, including authentication, authorization, validation, error handling, logging, and API documentation
• Experience with cloud-based AI and data platforms such as Microsoft Azure, Azure AI Foundry/Azure OpenAI, Azure Machine Learning, Databricks, or comparable platforms
• Experience with SQL and relational or NoSQL databases; understanding of data ingestion, transformation, data quality, and model-ready dataset creation
• Experience using GitHub, GitHub Actions, Docker, automated testing, code scanning, and CI/CD practices for AI and application development
• Experience deploying and monitoring scalable model-training and inference workloads, including batch and real-time patterns
• Solid understanding of supervised and unsupervised learning, feature engineering, model selection, validation, hyperparameter tuning, dimensionality reduction, classification, regression, clustering, and time-series or anomaly-detection approaches
• Proven ability to lead technical teams, decompose complex problems, estimate work, manage technical dependencies, mentor engineers, and drive delivery across the full software development lifecycle
• Solid analytical, problem-solving, decision-making, written communication, verbal communication, and stakeholder-management skills

Preferred Qualifications:

• Experience with Kubernetes, cloud-native deployment, infrastructure as code, and enterprise observability tools
• Experience with MLflow, Azure Machine Learning, Databricks, feature stores, model registries, vector databases, or comparable MLOps/LLMOps platforms
• Experience designing agentic AI workflows, tool/function calling, multi-agent patterns, and human-in-the-loop controls
• Experience with responsible AI governance, explain ability, fairness, privacy, security, and risk controls in regulated environments
• Healthcare domain experience and familiarity with handling sensitive or regulated data
• Experience leading proofs of concept and converting successful prototypes into secure, supportable, production-grade solutions

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.