Job Description

Role : Developer

Seeking AI/ML Engineers with 3–7 years of hands-on experience building scalable ML and GenAI solutions. Candidates must have strong healthcare domain exposure (claims, clinical data, provider/payor workflows). Prior Optum/UHG/UHC experience is highly preferred.
Key Responsibilities
AI/ML Engineering
• Build and deploy production grade ML, NLP, and LLM/GenAI models.
• Implement modern AI architecture patterns: microservices, feature stores, real time/batch inference, embeddings, and retrieval pipelines.
• Convert functional requirements into scalable AI solutions.
Model Development
• Develop and optimize models for claims automation, fraud detection, risk prediction, provider optimization, and document AI.
• Ensure models meet performance, reliability, and scalability standards.
Data & Integration
• Work with data engineering teams to integrate models with healthcare datasets (claims, EHR, clinical notes, PA/UM workflows).
• Ensure PHI/PII safe, compliant pipelines.
MLOps / Platform
• Implement CI/CD for ML/LLM workloads using MLflow, Vertex, SageMaker, Databricks, Airflow, Argo, and Kubernetes.
• Apply LLM Ops foundations for RAG and GenAI use cases.
Collaboration & Delivery
• Work cross functionally with product, cloud engineering, SMEs, and clinical teams.
• Participate in Agile processes and document reusable patterns and decisions.
Required Skills
• 3–7 years AI/ML engineering experience.
• Strong skills in Python (PyTorch/TensorFlow), NLP/LLMs/transformers, GenAI tooling, SQL, and data pipelines.
• Experience deploying ML/LLM systems in Azure/AWS/GCP.
• Solid understanding of U.S. healthcare data and compliant solution design (HIPAA, RBAC, audit logging).
• Experience working in ML Ops / LLM Ops environments.