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1–2 jobs· newest first

Developer Relations EngineerNew
Prime Intellect · San Francisco, US
On-site · Full-time · MidVisa
Staff Research Engineer, Hardware Intelligence
Nominal · New York, US
On-site · Full-time · Staff

+10K new in the last hour

Developer Relations Engineer

Prime Intellect · Posted Nov 12, 2026

San Francisco, California, United States
On-site
Full-time · Mid
Visa sponsorship

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AI

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Help developers build with Model Factory by creating documentation and practical tutorials that take them from a first training run to improving a model on their own tasks.

Compensation

Competitive base salary and equity.

Responsibilities

Own the Model Factory documentation, giving developers a clear path from their first quickstart to more advanced workflows with reliable API and SDK examples.
Build runnable tutorials that follow a model through the improvement cycle, from investigating failures in traces to designing evaluations and training with SFT or RL, with clear comparisons of results before deployment.
Work with Research and Applied Research to turn internal workflows into reproducible examples that developers can adapt to their own problems.
Partner with Engineering to publish documentation alongside new capabilities and maintain example code as the platform evolves.
Observe developers using Model Factory and work with Product and Engineering to resolve the points of confusion, whether they need a better explanation or a change to the product.

Requirements

Nice to have: open-source ML infrastructure
Nice to have: developer tools

Skills

Python LLM training LLM evaluation SFT RL prime-rl Verifiers

Benefits

Full medical, dental and vision coverage for employees and dependents
Flexible PTO
$200/month health and wellness benefit
Professional development budget for courses and conferences
Quarterly team off-sites, hackathons, conferences and learning opportunities

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Staff Research Engineer, Hardware Intelligence

Nominal · Posted Nov 9, 2026

New York, New York, United States
On-site
Full-time · Staff
8+ years

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Setting the research agenda for Hardware Intelligence, building agents that reason over hardware context, and leading the post-training of AI models.

Responsibilities

Set the research agenda for Hardware Intelligence: pick the problems, place the bets, and define what winning looks like each quarter.
Figure out how to store and represent hardware context, so agents reason over telemetry, test campaigns, requirements, designs, and simulations instead of retrieving them.
Teach agents to work the tools engineers already use, from CAD to simulation to analysis software, through computer use.
Connect simulation to the physical world: calibrate simulations against measured results, and use simulations to plan and explain tests.
Build distributed intelligence: collections of agents that coordinate across programs, fleets, and teams.

Requirements

Nice to have: post-training at a frontier lab
Nice to have: computer-use agents
Nice to have: multi-agent systems
Nice to have: knowledge representation
Nice to have: scientific ML

Skills

ML research RL reward models

Statistical rigor

AI coding agents

simulation software

Benefits

100% coverage of medical, dental, and vision insurance
Unlimited PTO and sick leave
Free lunch, snacks, and coffee
Professional Development Stipend
In-office hardware lab with a $250 project stipend

See full job description