ML/LLM Engineer - Applied AI

ATX Venture Partners; Austin (TX); On-site; USD 100,000 - 140,000; Full time

Benefits offered by this job

100% employer-paid health, vision, and dental insurance

Competitive compensation and benefits

Retirement plans (401k)

Disability insurance

Employee assistance programs

Job summary

Autonomize AI, located in Austin, Texas, is seeking a hands-on ML/LLM Engineer to develop impactful AI-native systems in healthcare. This mid to senior-level role involves optimizing machine learning pipelines, fine-tuning LLMs, and collaborating with engineering teams. Ideal candidates should have 3–6 years of applied ML experience, strong Python skills, and familiarity with ML frameworks like PyTorch. The company offers competitive compensation, 100% employer-paid health insurance, and growth opportunities within a dynamic team.

Qualifications

• 3–6 years of experience in applied ML with 1–2 years in LLMs.
• Strong Python skills and familiarity with frameworks.
• Experience in compliance-sensitive or healthcare environments.

Responsibilities

• Own and optimize ML pipelines for healthcare.
• Fine-tune and evaluate LLMs.
• Collaborate on real-world applications.

Skills

Applied ML experience

Python

ML frameworks (PyTorch, Transformers)

Experimentation and production deployment

Responsible AI practices

Healthcare experience

Tools

PyTorch

LangChain

LlamaIndex

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

• Own and optimize pipelines that combine classical ML and LLM‑based systems (RAG, scoring, summarization, etc.)
• Fine‑tune and evaluate LLMs using both open‑source and proprietary data
• Collaborate with product and engineering teams to build real‑world applications in healthcare and biopharma
• Implement retrieval strategies, prompt chaining, and inference orchestration for production use cases
• Monitor and improve model quality, latency, explainability, and safety
• Stay ahead of the curve in LLM evaluation, tuning, and agent‑based architectures

Qualifications

• 3–6 years of experience in applied ML, with at least 1–2 years working with LLMs
• Strong Python skills and familiarity with ML/LLM frameworks (PyTorch, Transformers, LangChain, LlamaIndex, etc.)
• Comfort with embeddings, vector search, retrieval pipelines, and prompt tuning
• Bias for experimentation, clarity, and pushing things into production — fast
• Understanding of responsible AI practices, model evaluation, and observability
• Experience in healthcare, compliance‑sensitive data, or regulated environments

What we offer

• A chance to make a real impact in the future of healthcare
• Autonomy, ownership, and the ability to chart your own growth path
• Competitive compensation and benefits
• 100% employer‑paid health, vision, and dental insurance
• Retirement plans (401k), disability insurance, employee assistance programs

How to Apply

Please submit your resume and a brief cover letter to [e-mail] 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!