Production AI Engineer — Healthcare Ops & LLMs

Autonomize, Inc; Austin, Northern (TX, KY); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Health insurance

Vision insurance

Dental insurance

401k retirement plan

Autonomy and ownership

Job summary

Autonomize AI in Austin, TX seeks a hands-on AI Engineer to ship real-world applications by building AI-powered pipelines that combine LLMs and classical ML. You will turn medical documents and forms into structured data and push models into production with robust retrieval, routing, and generation workflows.

You’ll collaborate with senior MLEs, product, and domain experts, iterate rapidly, and own components end-to-end from data ingestion to inference, with a strong focus on safety and

Qualifications

• 2+ years of applied ML and LLM experience.
• Strong Python and ML framework knowledge.
• Experience with embeddings, vector search and retrieval pipelines.
• Familiarity with model evaluation, observability, and responsible AI practices.
• Experience deploying models to production and MLOps tooling.

Responsibilities

• Build production AI pipelines combining LLMs and classical ML.
• Implement VLM- and OCR-based data extraction from healthcare documents.
• Fine-tune and adapt models with LoRA or similar techniques.
• Develop retrieval strategies, prompt chains, and tool-using agents.
• Create eval harnesses, run error analysis, and improve accuracy.
• Monitor model quality, latency, cost, and safety in production.
• Prototype new techniques and push suitable ones to production.
• Collaborate with senior MLEs, product, engineering, and domain experts.

Skills

ML with 2+ years

Python

PyTorch

HuggingFace Transformers

LangChain

LangGraph

LlamaIndex

Embeddings

Vector search

Prompt engineering

Model fine-tuning

MLOps

Docker

Kubernetes

Education

BS in Computer Science

MS in Data Science or related

Tools

MLflow

Docker

Kubernetes

LangChain

LangGraph

LlamaIndex

Transformers

Job description

Autonomize AI in Austin, TX seeks a hands-on AI Engineer to ship real-world applications by building AI-powered pipelines that combine LLMs and classical ML. You will turn medical documents and forms into structured data and push models into production with robust retrieval, routing, and generation workflows.

You’ll collaborate with senior MLEs, product, and domain experts, iterate rapidly, and own components end-to-end from data ingestion to inference, with a strong focus on safety and