Associate AI/ML Engineer

Requisition Number: 2366767
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:

• Assist in building and improving machine learning and Generative AI solutions for claims automation, unlisted code analysis, and anomaly detection
• Support development of LLM-based applications, including prompt engineering, fine-tuning support, and basic RAG pipeline implementation
• Develop and maintain data pipelines and feature engineering workflows using Python and PySpark
• Work with large healthcare datasets to build and evaluate ML models (classification, NLP, anomaly detection)
• Contribute to embedding pipelines and vector database integrations for search and retrieval use cases
• Collaborate with senior engineers, product teams, and domain experts to understand business problems (e.g., MRR workflows, coding validation) and assist in solution development
• Help monitor model performance and support improvements in accuracy, latency, and reliability
• Document approaches, experiments, and results, and communicate findings to team members
• 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:

• 2+ years of experience in machine learning, data science, or AI/ML engineering (1+ years acceptable for exceptional candidates with strong projects/internships)
• Experience working with data processing tools (Pandas, SQL; exposure to PySpark is a plus)
• Basic understanding of machine learning concepts (training, evaluation, overfitting, feature engineering)
• Familiarity with cloud platforms (Azure/AWS/GCP) or willingness to learn
• Proven solid programming skills in Python and basic experience with ML libraries (scikitlearn, PyTorch, or TensorFlow)
• Proven exposure to NLP or LLM-based applications through work, internships, or projects
• Proven good problem-solving skills and ability to learn quickly in a fast-paced environment
• Proven solid communication skills and ability to work collaboratively in a team setting

Preferred Qualifications:

• Internship or project experience in healthcare, claims data, or related domains
• Basic understanding of APIs, model deployment, or backend integration
• Familiarity with GenAI tools/frameworks (e.g., HuggingFace, LangChain, LlamaIndex, OpenAI/Azure OpenAI APIs)
• Proven exposure to Generative AI concepts such as:
  • Prompt engineering
  • Retrieval Augmented Generation (RAG)
  • Embeddings and semantic search
• Proven exposure to Spark/PySpark or distributed data processing
• Demonstrated hands-on projects (GitHub, academic work, or hackathons) involving ML or GenAI

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.