ML/LLM Engineer - Applied AI
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At a glance
Job overview
Autonomize is hiring a ML/LLM Engineer - Applied AI. Autonomize AI is seeking a hands-on ML/LLM Engineer to build and optimize AI-native systems for healthcare. This role involves working with structured and unstructured data to power decisions in high-stakes domains. The engineer will focus on applied ML problems, from retrieval to routing to generation, and ship impactful solutions.
Key focus areas include Own and optimize pipelines that combine classical ML and LLM-based systems, Fine-tune and evaluate LLMs using both open-source and proprietary data, and Collaborate with product and engineering teams to build real-world applications.
Successful candidates bring 3–6 Years Applied ML Experience, 1–2 Years LLM Experience, and Experience In Healthcare Or Regulated Environments. Important skills include Machine Learning, LLM, Python, PyTorch, Transformers, and LangChain.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
About Autonomize AI Autonomize AI is revolutionizing healthcare by streamlining knowledge workflows with AI. We reduce administrative burdens and elevate outcomes, empowering professionals to focus on what truly matters — improving lives. We're growing fast and looking for bold, driven teammates to join us. The Opportunity We're looking for a hands-on ML/LLM Engineer who’s excited to ship real-world applications — not just benchmarks. You’ll help us build and optimize AI-native systems that blend structured and unstructured data to power decisions in high-stakes domains. This is a mid to senior-level role for someone who’s ready to go deep on applied ML problems — from retrieval to routing to generation — and ship solutions that deliver impact. What you'll do
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Own and optimize pipelines that combine classical ML and LLM-based systems (RAG, scoring, summarization, etc.)
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Fine-tune and evaluate LLMs using both open-source and proprietary data
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Collaborate with product and engineering teams to build real-world applications in healthcare and biopharma
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Implement retrieval strategies, prompt chaining, and inference orchestration for production use cases
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Monitor and improve model quality, latency, explainability, and safety
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Stay ahead of the curve in LLM evaluation, tuning, and agent-based architectures
Qualifications
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3–6 years of experience in applied ML, with at least 1–2 years working with LLMs
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Strong Python skills and familiarity with ML/LLM frameworks (PyTorch, Transformers, LangChain, LlamaIndex, etc.)
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Comfort with embeddings, vector search, retrieval pipelines, and prompt tuning
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Bias for experimentation, clarity, and pushing things into production — fast
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Understanding of responsible AI practices, model evaluation, and observability
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Experience in healthcare, compliance-sensitive data, or regulated environments What we offer
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A chance to make a real impact in the future of healthcare
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Autonomy, ownership, and the ability to chart your own growth path
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Competitive compensation and benefits
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100% employer-paid health, vision, and dental insurance
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Retirement plans (401k), disability insurance, employee assistance programs
How to Apply Please submit your resume and a brief cover letter to [email protected] explaining why you are the ideal candidate for this role. We are excited to meet someone who is eager to bring their skills, enthusiasm, and creativity to our team!
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