Machine Learning Engineer/AI Engineer
Role details
Job location
Tech stack
Job description
Work at the intersection of applied AI, data science, and software engineering, building, optimizing, and integrating machine learning (ML) and large language model (LLM) solutions. 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., * 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
Requirements
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
- Position is remote, but candidates based in Raleigh/Durham/Cary, NC or DC area preferred. *, * 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, * 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)
Benefits & conditions
Benefits are a key component of your rewards package. Our benefits are designed to provide you with additional protection, security, and support for both your career and your life away from work. Our benefits include comprehensive health plans, paid time off, retirement savings, corporate wellness, educational assistance, corporate discounts, and more.
Compensation
The pay range for this position is listed below.
"Based on our compensation philosophy, an applicant's position placement in the pay range will depend on various considerations, such as years of applicable experience and skill level."