Machine Learning Development

Job title: Machine Learning Development

UnitedHealth Group

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: Machine Learning Development Design, develop, train, evaluate, and deploy machine learning models supporting: Predictive analytics Forecasting Recommendation systems Classification and regression Anomaly detection Translate business requirements into scalable AI/ML solutions Apply machine learning, statistical modeling, and data science techniques to solve business problems Perform exploratory data analysis (EDA), feature engineering, data preparation, and model experimentation Work with structured, semi-structured, and unstructured datasets AI/ML Engineering & Model Lifecycle Build and maintain machine learning pipelines supporting: Data ingestion Feature engineering Model training Model validation Model deployment Monitoring and retraining Implement model evaluation, benchmarking, and performance measurement processes Support model optimization and hyperparameter tuning activities Contribute to repeatable and scalable AI engineering practices MLOps & Production Deployment Deploy machine learning models using APIs, containerized services, and cloud-native platforms Contribute to reusable AI components, frameworks, and engineering assets Monitoring & Operational Excellence Monitor deployed models for: Accuracy Drift Latency Reliability Operational health Support implementation of observability capabilities including monitoring, logging, alerting, and performance reporting Participate in troubleshooting, root cause analysis, and production support activities Help ensure AI solutions meet enterprise standards for reliability and operational excellence Data Engineering & AI Integration Collaborate with data engineering teams to develop scalable data pipelines and feature engineering workflows Integrate AI and machine learning capabilities into enterprise applications, APIs, and business processes Support development of reusable features and AI services for enterprise consumption Responsible AI & Governance Follow Responsible AI practices related to explainability, fairness, transparency, and governance Support model validation, auditability, and compliance activities Adhere to organizational security, privacy, and governance standards Emerging AI Technologies Explore emerging AI, Generative AI, and Agentic AI technologies and contribute to innovation initiatives Support implementation of AI capabilities including: Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Embeddings Semantic Search Contribute to engineering best practices and continuous improvement initiatives 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 degree in computer science, Data Science, Engineering, Mathematics, Statistics, Artificial Intelligence, or related field 5+ years of experience in Machine Learning, Artificial Intelligence, Data Science, Software Engineering, or related disciplines Experience developing and deploying machine learning solutions in enterprise or cloud environments Experience building machine learning pipelines and production-ready AI solutions Experience working with APIs, cloud-based AI services, and distributed data platforms Experience integrating AI/ML solutions into business applications and workflows Knowledge of model monitoring, performance evaluation, and production support processes Solid understanding of: Machine Learning Statistical Modeling Predictive Analytics Model Evaluation Feature Engineering Familiarity with MLOps practices including model deployment, monitoring, experiment tracking, and lifecycle management Solid programming skills in Python and SQL Understanding of Responsible AI, model governance, and compliance requirements Proven solid analytical, problem-solving, communication, and collaboration skills nPreferred Qualifications: Experience deploying machine learning solutions using Azure ML, SageMaker, Vertex AI, MLflow, Kubeflow, or similar platforms Experience with distributed data processing technologies including Spark, Databricks, PySpark, Kafka, or modern data engineering platforms Experience developing machine learning and deep learning solutions using TensorFlow, PyTorch, or equivalent frameworks Experience with Generative AI technologies including: Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Embeddings Semantic Search Agentic AI concepts Experience integrating AI services and model APIs into enterprise applications Experience contributing to reusable AI frameworks, engineering accelerators, or platform capabilities Experience working within healthcare, financial services, insurance, or other regulated industries Familiarity with model monitoring, observability, and operational analytics practices Familiarity with NLP, recommendation systems, forecasting, anomaly detection, or intelligent automation solutions Understanding of Responsible AI, model risk management, and governance frameworks Contributions to AI innovation initiatives, open-source projects, technical publications, or enterprise transformation efforts

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.