Founding AI Engineer

What you'll do

• Build reliable agentic workflows, high-recall retrieval, synthesis, and evaluation systems.
• Optimize model inference and serving, including small models in constrained, air-gapped environments.
• Adapt and post-train models, including research into reinforcement learning; later set AI direction and grow the team.

What they ask for

• Have trained or post-trained real models through fine-tuning, RLHF, or RL; API-calling experience alone is insufficient.
• Have shipped LLM or agentic systems to production for real users.
• Have strong evaluation instincts and hands-on inference and serving experience.
• Include a link to a repo, paper, write-up, or system you built when applying.

Nice to have

• Experience on a big tech AI team or at an AI startup.
• A PhD or MS in ML; research publications or open-source work in LLMs, agents, RL, or evaluation; or distributed training or large-scale GPU experimentation.

Pay

$170K – $250K USD base salary

Tools

vLLM, H100, H200 GPUs, Python, PostgreSQL, Elasticsearch, Kubernetes (K8s), Vue.js

AI focus

Build and operate agentic systems, retrieval and evaluation, inference optimization, fine-tuning, model adaptation, post-training, and RL for legal discovery, including deployment in air-gapped environments.