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 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