Job Description
Role: AI/ML Engineer Location: Remote Position Overview The candidate will be responsible for designing, developing, and deploying machine learning models and AI-driven solutions to support healthcare analytics, improve operational efficiency, and drive business insights. This role requires strong expertise in machine learning, data engineering, cloud platforms, and end-to-end model lifecycle management. Key Responsibilities • Develop and implement scalable machine learning models for predictive analytics, classification, NLP, and optimization use cases. • Work closely with data engineers and analysts to gather requirements, understand business problems, and translate them into ML solutions. • Perform data preprocessing, feature engineering, model tuning, and validation. • Build reusable ML pipelines and automate workflows through MLOps frameworks. • Deploy models into production using cloud-native services (Azure, AWS, or GCP). • Monitor and optimize model performance and ensure long-term model stability. • Collaborate cross-functionally with product, engineering, and business stakeholders within Optum. • Document solution designs, model behavior, and deployment architecture. Mandatory Skills • Strong programming skills in Python (NumPy, Pandas, Scikit-learn, TensorFlow / PyTorch). • Experience building ML models end-to-end, including training, validation, deployment, and monitoring. • Hands-on experience with NLP, LLMs, or generative AI technologies (Hugging Face, LangChain preferred). • Knowledge of cloud platforms such as Azure, AWS, or GCP (Optum widely uses Azure & GCP). • Familiarity with MLOps tools such as MLflow, Kubeflow, Vertex AI, SageMaker, or Azure ML Studio. Apply tot his job