aimlroles

Senior Machine Learning Engineer (LLMs)

Albi Open · verified Oct 22, 2026
On-site Chicago Full-time Senior Machine Learning Engineering

At a glance

Senior Machine Learning Engineering role at Albi. Chicago · full-time · no salary stated · we estimate $150,938–$212,053.

Estimated pay

Albi has not published a salary for this role. The figure below is our estimate, not theirs.

$150,938 – $212,053
What the middle half of senior machine learning engineering roles in Chicago paid, among postings that did state a salary.
Worked out from 6 postings that stated pay, median $172,856. Last updated Oct 22, 2026.
RoleMachine Learning Engineering
SenioritySenior
LocationChicago
WorkplaceOn-site
EmploymentFull-time
PostedMar 9, 2026 · 7mo ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Design, train, evaluate and refine LLM systems from initial architecture through ongoing iteration
  • Adapt existing models with techniques such as LoRA, instruction tuning and RLHF
  • Create data pipelines that bring together product databases, documents, APIs and logs
  • Put monitored models into production with reliability measures and clear guardrails
  • Work with product and engineering teams, and help build and coordinate the AI engineering group

What you bring

  • At least five years of hands-on ML or AI engineering experience
  • You have helped train LLMs substantially, beyond using model APIs
  • You understand transformers, attention mechanisms and how models behave during training
  • You code in Python and use PyTorch or JAX, with experience in large data pipelines and experiment tracking
  • You have fine-tuned models and use Claude Code routinely in your development workflow

Who this fits

This senior role suits an engineer who enjoys digging into how models work, tackling difficult technical problems and owning projects through delivery. You’ll also explain complex systems to both technical experts and non-technical partners, and mentor other engineers. The role is onsite in Chicago.

From the employer

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