Meaningful work,
meaningful life

Key Responsibilities:

• Develop and deploy ML models for anomaly detection, risk scoring, and provider profiling

• Build feature engineering pipelines using claims and provider data

• Integrate GenAI capabilities into FWA workflows, such as:

  • Auto-generation of fraud investigation summaries

  • Intelligent querying of claims data using natural language

• Implement RAG-based pipelines to combine claims data with guidelines

• Build and deploy APIs/services for both ML models and LLM-based applications

• Optimize performance, scalability, and cost of ML + GenAI workloads

• Collaborate with data scientists and architects on hybrid AI solutions

Required Skills & Experience:

• 6–9 years of experience in ML engineering

• Strong expertise in Python (Pandas, Scikit-learn, PySpark)

• Experience deploying ML models (APIs, Docker, pipelines)

• Hands-on exposure to GenAI/LLMs:

  • Prompt engineering

  • Embeddings & vector databases

  • RAG pipelines

• Experience with cloud platforms like Amazon Web Services

• Strong SQL and data pipeline experience