AI/ML Engineer

Key responsibilities

Build, train, evaluate and deploy ML models and LLM/GenAI-based solutions into production.

Develop ML pipelines, feature stores and serving infrastructure; monitor model performance and drift.

Collaborate with product and engineering to integrate AI capabilities into customer-facing workflows.

Translate ambiguous business problems into well-scoped, measurable AI solutions.

Skills

Python SQL AWS

Hands-on ML engineering in Python (PyTorch/TensorFlow/scikit-learn); SQL for feature and data work; deploying ML workloads on AWS (SageMaker, Bedrock, Lambda, S3).

LLM / GenAI, RAG, prompt engineering, vector databases.

MLOps tooling (MLflow, Kubeflow, model registries).

Healthcare data and clinical NLP experience