Machine Learning Engineer/AI Engineer

Acentra Health, LLC•Raleigh, NC

19h•Remote

About The Position

Acentra Health is looking for a Machine Learning Engineer/AI Engineer to join their growing team. This role involves working at the intersection of applied AI, data science, and software engineering, focusing on building, optimizing, and integrating machine learning (ML) and large language model (LLM) solutions. The position 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 will have experience deploying ML/LLM solutions in production, exposure to MLOps/LLMOps, and a strong ability to mentor engineers. They should combine technical excellence with problem-solving skills to deliver scalable, compliant, and impactful AI solutions in the healthcare domain. The position is remote, with a preference for candidates based in the Raleigh/Durham/Cary, NC or DC area.

Requirements

Bachelor’s degree in computer science, Data Science, or related field (Master's or 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

Nice To Haves

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)

Responsibilities

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