Acentra HealthRemote
Machine Learning Engineer/AI Engineer
United States
Full-time
2 weeks ago
$97,000 - $130,000 USD
H1B Sponsor Likely
Key skills
PythonML/AI frameworksLLMsembeddingsMLOps/LLMOpsCloud experienceAPI developmentHealthcare domain experiencecommunicationMentoring skillsAIMachine LearningMLGenAILLMPyTorchTensorFlowscikit-learnHugging FaceLangChainMLOpsPineconeWeaviateAWSAzureCI/CDMentoringCommunication
About this role
Acentra Health is dedicated to empowering better health outcomes through technology and clinical expertise. They are seeking a Machine Learning Engineer/AI Engineer to work at the intersection of applied AI, data science, and software engineering, focusing on building and optimizing machine learning solutions to improve healthcare outcomes.
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
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
- 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)