Experience shipping LLM features in production SaaS
Open‑source contributions or published work or patents in ML / NLP
Microsoft Foundry experience
Skills
Python
PyTorch
JAX
LoRA
FSDP
DeepSpeed
Megatron
vLLM
Triton
Claude Code
Benefits
Health insurance
Dental insurance
Vision insurance
401(k)
PTO
Equipment budget
Learning budget
About the role
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.
Responsibilities
You will:
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Own end‑to‑end LLM systems: architecture, training, evals, and iteration
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Fine‑tune and extend existing models (LoRA, instruction tuning, RLHF)
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Build and maintain data pipelines from product databases, documents, APIs, and logs
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Ship reliable, monitored, production models with clear guardrails
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Collaborate closely with product and engineering to turn messy real‑world problems into working systems
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Build and coordinate the AI engineering team
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Use Claude Code as a core tool for development, refactors, tests, and experiments
This is for you if:
Requirements
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“How does this actually work under the hood?” is your default question
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You’re fine sitting with a hard problem for days and reading papers on weekends to figure it out
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If there’s something interesting to learn or solve, it doesn’t matter if it’s Saturday or 1 a.m., you’re in
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You build side projects nobody asked for and write cleaner code than anyone requires
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You’re quietly competitive, self‑taught in at least one major skill, and think in systems
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You’re slightly allergic to meetings without a clear purpose or owner
Requirements
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5+ years of real world experience in ML / AI engineering
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Proven experience training or substantially contributing to training LLMs (not just calling APIs)
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Deep understanding of transformers, attention, and training dynamics
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Strong Python plus PyTorch or JAX
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Experience with large‑scale data pipelines and experiment tracking
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Hands‑on fine‑tuning (LoRA, instruction / SFT, RLHF or similar)
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Comfortable using Claude Code as part of your daily workflow
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Able to explain complex systems simply to non‑technical stakeholders and go deep with experts
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Track record of owning projects end‑to‑end and mentoring other engineers
Nice to have
Nice to have:
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Distributed training (FSDP, DeepSpeed, Megatron, etc.)