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. Compensation: $130,000.00 per year