AI/ML Engineer

Role Overview

Senior AI/ML Engineer to transform AI/ML prototypes (including LLMs and predictive models) into scalable, reliable production systems. You will collaborate with Data Scientists, Data Engineers, and Product teams to design and deploy AI/ML pipelines with healthcare regulatory compliance.

Key Responsibilities

• Build and maintain end-to-end ML pipelines: data ingestion → feature engineering → model training → deployment → monitoring
• Productionize models into APIs, batch, and streaming workflows
• Develop LLM-powered workflows (document extraction, classification, summarization, RAG pipelines)
• Implement OCR / Document AI solutions for structured and unstructured data (e.g., AWS Textract, DBX OCR)
• Build vector databases and embedding-based retrieval systems
• Apply MLOps best practices (CI/CD, model versioning, lineage tracking, automated retraining)
• Work with Databricks (Delta Lake, Unity Catalog, Workflows) and AWS (S3, Lambda, Bedrock)
• Optimize performance for latency, throughput, and cost
• Ensure HIPAA and healthcare compliance with secure handling of sensitive data
• Mentor junior engineers and share production ML best practices

Required Qualifications

• 6+ years in ML engineering / AI engineering / software engineering
• Strong proficiency in Python and SQL
• Experience deploying ML models into production
• Experience with Databricks, PySpark, and distributed data processing
• Familiarity with ML lifecycle tools: MLflow, model registries, monitoring frameworks
• Ability to build inference APIs (FastAPI, Flask, etc.)
• Knowledge of LLM workflows, embeddings, and vector search
• Experience with OCR / Document AI pipelines
• Strong problem-solving, attention to detail, and communication skills

Preferred Qualifications

• Healthcare data experience (EHR, claims, FHIR/HL7)
• Docker and Kubernetes
• Familiarity with CMS or federal healthcare programs
• Knowledge of HIPAA, HITRUST, or NIST frameworks

Location / Schedule

• Remote role primarily working EST hours.