High PriorityHire in 2-4 weeks$4,500–$8,000 / monthPythonPyTorchLLMs
AI / ML Engineer
Build intelligent systems and advance our AI capabilities.
You will turn model calls into product behavior operators can trust. That means evals, limits, citations, and a failure mode a person can understand — not a demo that only works on the happy path. The stack is practical: Python for training and evaluation, PyTorch where a model needs to be trained or adapted, and LLMs where a workflow should summarize, classify, or take a bounded action.
We want production AI with measurement. A notebook that cannot be monitored after launch is not enough.
What you'll work on
- LLM workflows for summaries, triage, and internal tools
- Evaluation sets and regression checks before a prompt or model change ships
- PyTorch training or adaptation when a general model is the wrong tool
- Latency, cost, and failure visibility for model-backed services
- Safe defaults around secrets, rate limits, and data that must not leave the product
Requirements
- Shipped AI or LLM features in production, with monitoring
- Strong Python and working knowledge of PyTorch
- Experience with structured outputs, tool use, or evaluation harnesses
- Examples you can walk through: a repo, a write-up, or a system you maintained
Nice to have
- Retrieval, ranking, or citation quality work
- TypeScript services in front of a model
How to apply
- Put a relevant GitHub repository or live demo near the top of your note.
- Attach a PDF resume with concrete outcomes: what shipped, what changed, and the part you owned.
- Include your time zone, weekly availability, and earliest start date.
- Applications without a work sample we can review are unlikely to move forward.
Submit application
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