Senior Machine Learning Engineer (LLMs)

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 iterationFine‑tune and extend existing models (LoRA, instruction tuning, RLHF)Build and maintain data pipelines from product databases, documents, APIs, and logsShip reliable, monitored, production models with clear guardrailsCollaborate closely with product and engineering to turn messy real‑world problems into working systemsBuild and coordinate the AI engineering teamUse Claude Code as a core tool for development, refactors, tests, and experimentsThis is for you if:“How does this actually work under the hood?” is your default questionYou’re fine sitting with a hard problem for days and reading papers on weekends to figure it outIf there’s something interesting to learn or solve, it doesn’t matter if it’s Saturday or 1 a.m., you’re inYou build side projects nobody asked for and write cleaner code than anyone requiresYou’re quietly competitive, self‑taught in at least one major skill, and think in systemsYou’re slightly allergic to meetings without a clear purpose or owner

5+ years of real world experience in ML / AI engineeringProven experience training or substantially contributing to training LLMs (not just calling APIs)Deep understanding of transformers, attention, and training dynamicsStrong Python plus PyTorch or JAXExperience with large‑scale data pipelines and experiment trackingHands‑on fine‑tuning (LoRA, instruction / SFT, RLHF or similar)Comfortable using Claude Code as part of your daily workflowAble to explain complex systems simply to non‑technical stakeholders and go deep with expertsTrack record of owning projects end‑to‑end and mentoring other engineersNice to have:Distributed training (FSDP, DeepSpeed, Megatron, etc.)Inference optimization (quantization, speculative decoding, vLLM, Triton)Experience shipping LLM features in production SaaSOpen‑source contributions or published work or patents in ML / NLPMicrosoft Foundry experience

Competitive salary (based on experience and location)Generous PTOMedical, dental, and vision coverage401(k) planHigh ownership and autonomy over your workDirect collaboration with a small team of smart, kind, motivated engineersAn environment that values deep work, clear thinking, and real impactRegular team events and off‑sitesEquipment and learning budget to help you do your best work and keep up with the frontier