Key Responsibilities

" Build and deploy full ML pipelines: data ingestion, feature engineering, model training, evaluation, deployment, and monitoring.

" Develop GenAI/LLM solutions, including RAG, vector search, fine tuning, and prompt optimization.

" Build scalable Python-based services/APIs using TensorFlow/PyTorch, FastAPI/Flask, and cloud technologies.

" Implement MLOps practices with MLflow/Kubeflow/SageMaker/Azure ML, CI/CD, and automated orchestration (Airflow, Prefect, Autosys).

" Ensure data quality, security, and compliance with model governance (SR 11 7), explainability, and financial regulatory standards.

" Collaborate with cross functional teams to translate business needs into AI solutions; provide mentorship and perform code/design reviews.



Required Qualifications

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