Acentra Health, LLC-posted 2 months ago
$97,040 - $130,000/Yr
Full-time • Mid Level
Raleigh, NC

Acentra Health is looking for a Machine Learning Engineer/AI Engineer to join our growing team. This role emphasizes generative AI (GenAI), retrieval-augmented generation (RAG), and natural language processing (NLP) to drive innovation, improve healthcare outcomes, and create operational efficiencies. The ideal candidate has experience deploying ML/LLM solutions in production, exposure to MLOps/LLMOps, and a strong ability to mentor engineers. They combine technical excellence with problem-solving skills to deliver scalable, compliant, and impactful AI solutions in the healthcare domain.

  • Design, develop, and deploy LLM-powered applications (e.g. summarization, intelligent assistants, document processing, automation)
  • Strong skills in API development and system integration, with the ability to contribute across the full stack
  • Build and optimize RAG pipelines using embeddings and vector databases (e.g., Pinecone, Weaviate, FAISS)
  • Support ML pipelines including data preparation, training workflows, and deployment into applications
  • Support and implement MLOps/LLMOps practices such as CI/CD pipelines, versioning, monitoring, retraining, and governance
  • Mentor and coach engineers on best practices, solution architecture, and applied AI strategies
  • Partner with business and product teams to translate requirements into effective AI solutions
  • Stay current on advances in LLMs, GenAI, and compliance requirements (HIPAA, GDPR, FDA)
  • Read, understand, and adhere to all corporate policies including policies related to HIPAA and its Privacy and Security Rules
  • Master’s degree in computer science, Data Science, or related field (PhD preferred)
  • 4+ years of experience as an ML/AI Engineer with proven applied AI/LLM deployments
  • Proficiency in Python and ML/AI frameworks (TensorFlow, PyTorch, Hugging Face, scikit-learn)
  • Hands-on experience with LLMs, embeddings, vector DBs, and RAG pipelines
  • Cloud experience with AWS and Azure for deploying and managing AI systems
  • Familiarity with MLOps/LLMOps and CI/CD practices
  • Experience deploying ML/LLM systems in healthcare or other regulated environments
  • Excellent communication skills and experience mentoring and collaborating with engineers
  • Experience with LangChain, LlamaIndex, or agentic AI frameworks (AutoGen, CrewAI, Semantic Kernel)
  • Exposure to multi-agent system design and implementation
  • Knowledge of healthcare data standards (HL7, FHIR) and compliance (HIPAA)
  • Comprehensive health plans
  • Paid time off
  • Retirement savings
  • Corporate wellness
  • Educational assistance
  • Corporate discounts
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