Role: Senior AI/ML Engineer (Vector Store & Retrieval Systems)

Location: Remote

10+ years in AI/ML or Data Engineering (healthcare domain preferred) to design, benchmark, and optimize text embedding and vector search solutions for large-scale clinical data. This role focuses on building high-performance pipelines and evaluating AI models to support intelligent search across patient records.

Key Responsibilities:

Develop and benchmark text chunking and embedding strategies

Evaluate embedding models (OpenAI, Cohere, SBERT, etc.)

Design and optimize vector search systems

Build scalable pipelines for large datasets (up to billions of documents)

Measure performance across cost, speed, scalability, and accuracy

Support near real-time indexing and high query workloads

Ensure compliance with PHI/HIPAA and enterprise security standards

Required Skills:

Strong experience in AI/ML and NLP (embeddings, transformers)

Hands-on with LLMs, RAG, and vector databases

Proficiency in Python and data frameworks (Spark/Databricks)

Experience with cloud platforms (Azure/AWS/GCP)

Knowledge of distributed systems and high-throughput pipelines

Understanding of healthcare data and PHI compliance

This is a remote position.