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Open nowPosted 209 days ago

Senior Machine Learning Engineer (LLMs)

Workable (global search)108,016 open roles

Where
Chicago, IL, United States
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Your applicationOpen nowSenior Machine Learning Engineer (LLMs)Workable (global search) · Chicago, IL, United States
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7.9% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 7 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.0%30 days
This job: posted 209 days ago

Workable (global search) median: 7 days open

The posting

We’re building deeply integrated LLMs into a real product used daily by restoration companies running thousands of jobs. This is not a “prompt engineer” role. You’ll design, train, and ship domain-specific language models that automate real workflows and move real revenue.

You will:

  • Own end‑to‑end LLM systems: architecture, training, evals, and iteration
  • Fine‑tune and extend existing models (LoRA, instruction tuning, RLHF)
  • Build and maintain data pipelines from product databases, documents, APIs, and logs
  • Ship reliable, monitored, production models with clear guardrails
  • Collaborate closely with product and engineering to turn messy real‑world problems into working systems
  • Build and coordinate the AI engineering team
  • Use Claude Code as a core tool for development, refactors, tests, and experiments

This is for you if:

  • “How does this actually work under the hood?” is your default question
  • You’re fine sitting with a hard problem for days and reading papers on weekends to figure it out
  • If there’s something interesting to learn or solve, it doesn’t matter if it’s Saturday or 1 a.m., you’re in
  • You build side projects nobody asked for and write cleaner code than anyone requires
  • You’re quietly competitive, self‑taught in at least one major skill, and think in systems
  • You’re slightly allergic to meetings without a clear purpose or owner

Requirements

  • 5+ years of real world experience in ML / AI engineering
  • Proven experience training or substantially contributing to training LLMs (not just calling APIs)
  • Deep understanding of transformers, attention, and training dynamics
  • Strong Python plus PyTorch or JAX
  • Experience with large‑scale data pipelines and experiment tracking
  • Hands‑on fine‑tuning (LoRA, instruction / SFT, RLHF or similar)
  • Comfortable using Claude Code as part of your daily workflow
  • Able to explain complex systems simply to non‑technical stakeholders and go deep with experts
  • Track record of owning projects end‑to‑end and mentoring other engineers

Nice to have:

  • Distributed training (FSDP, DeepSpeed, Megatron, etc.)
  • Inference optimization (quantization, speculative decoding, vLLM, Triton)
  • Experience shipping LLM features in production SaaS
  • Open‑source contributions or published work or patents in ML / NLP
  • Microsoft Foundry experience

Benefits

  • Competitive salary (based on experience and location)
  • Generous PTO
  • Medical, dental, and vision coverage
  • 401(k) plan
  • High ownership and autonomy over your work
  • Direct collaboration with a small team of smart, kind, motivated engineers
  • An environment that values deep work, clear thinking, and real impact
  • Regular team events and off‑sites
  • Equipment and learning budget to help you do your best work and keep up with the frontier
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