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.
We are seeking a talented and passionate AI/ML Engineer to join our innovative technology team. The ideal candidate will be at the heart of designing and building the intelligent systems that power our products and services. This role involves working on the complete lifecycle of machine learning projects, from data collection and preprocessing to model development, deployment, and maintenance. You will be a key player in transforming complex data into actionable insights and creating AI-driven solutions that solve real-world problems.
Primary Responsibilities:
- Design and Develop ML Models: Research, design, and develop machine learning and deep learning models to address business challenges. This includes everything from selecting the right algorithms to building predictive models from the ground up
- Data Pipeline and Preprocessing: Build and maintain robust data pipelines. You will be responsible for gathering data from various sources, cleaning it, and transforming it into a usable format for model training
- Model Training and Evaluation: Train, test, and validate machine learning models to ensure they are accurate, reliable, and meet business requirements. This involves performing statistical analysis and running experiments to optimize model performance
- Deployment and MLOps: Deploy trained models into production environments and maintain their lifecycle. You will implement MLOps best practices for monitoring, retraining, and updating models to ensure they remain effective over time.
- Collaboration and Innovation: Work closely with data scientists, software engineers, and product managers to integrate AI/ML models into our applications and systems
- Stay Current: Keep up-to-date with the latest advancements in the field of AI, machine learning, and deep learning, and be prepared to apply new research to our products.
- Build Generative AI and LLM Workflows: Design, develop, and optimize LLM-powered applications and agentic workflows - including retrieval-augmented generation (RAG), prompt engineering, tool/function calling, and multi-step orchestration - to deliver production-grade generative AI features
- Ensure LLM Reliability and Evaluation: Establish evaluation frameworks, guardrails, and structured, type-safe output validation to ensure generative AI systems are accurate, safe, cost-efficient, and reliable in production
- 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:
- Technical Skills:
- Hands-on experience with ML frameworks and libraries such as TensorFlow, PyTorch, Keras, and Scikit-learn
- Experience building LLM workflows and agentic applications using orchestration frameworks such as LangGraph and LangChain
- Hands-on experience integrating LLM provider APIs (e.g., Anthropic Claude, OpenAI, Azure OpenAI) into applications
- Deep understanding of machine learning, deep learning, and statistical modeling concepts
- Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) and their machine learning services (Databricks)
- Familiarity with core generative AI concepts including retrieval-augmented generation (RAG), prompt engineering, embeddings, and vector databases (e.g., Pinecone, FAISS, Chroma)
- Solid programming proficiency in languages like Python, R, or Java
- Proficiency in data handling, including SQL, and experience with data processing tools like Pandas and NumPy
- Proficiency with Pydantic for data validation and enforcing structured, type-safe outputs from LLMs
- Soft Skills:
- Solid analytical and problem-solving abilities
- Excellent communication skills to articulate complex technical concepts to diverse audiences
- A creative and proactive mindset with a drive for continuous improvement
Preferred Qualifications:
- Experience with containerization technologies like Docker and Kubernetes
- Proven experience deploying and managing machine learning models in a production environment
- Experience with LLM observability and evaluation tooling, fine-tuning, or prompt-optimization techniques
- Previous experience on databrick
- Experience with contributions to open-source projects or a solid portfolio of relevant personal projects
- Knowledge of MLOps principles and tools
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.