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Research / Data Engineer - Post-Training & RL | San Francisco

  • Research / Data Engineer - Post-Training & RL | San Francisco job type Posted on: Nov 12, 2026
  • Research / Data Engineer - Post-Training & RL | San Francisco experience level RnB Consultancy
  • Research / Data Engineer - Post-Training & RL | San Francisco employment type San Francisco, Texas
  • Research / Data Engineer - Post-Training & RL | San Francisco salary Salary: $300,000 per year
  • Research / Data Engineer - Post-Training & RL | San Francisco employment type Onsite
  • Research / Data Engineer - Post-Training & RL | San Francisco salary Full-time

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Job Title :

Research / Data Engineer - Post-Training & RL | San Francisco

Job Type :

Full-Time

Job Location :

San Francisco Texas United States

Remote :

No

Jobcon Logo Job Description :

Job Description

Job Description

Researcher or engineer? This role wants both, in one person.

A profitable, seed-stage AI company in San Francisco creates long-horizon reinforcement learning environments and post-training data for leading AI labs in the US and abroad. Most data providers solve demand by adding people. This team treats post-training data as a research problem and scales it with processes that improve themselves. Demand for their data is bigger than what they can deliver today, so they're growing a small, very strong core team of researchers and engineers.

What you'll own

  • The full post-training loop: infrastructure, training runs and the data that goes into them
  • Long-horizon RL environments and tasks in many fields, from science to ML research itself
  • Scaling data generation through smarter, self-improving tooling, not more headcount
  • Judging which real-world tasks are worth building, because they matter to the labs and the economy

What you bring

  • Real depth in ML research (think post-training, RL, evals or interpretability) and serious engineering skills
  • You've post-trained models yourself and built the datasets for it
  • A good eye for data, or the research ability to build that eye fast
  • You read code fast and solve problems quickly in PyTorch and ML pipelines
  • Curiosity that shows: papers, side projects, open source contributions or writing
  • Roughly 3–7 years of experience

Bonus points

  • Both published research and things you actually shipped
  • Domain depth next to ML, such as neuroscience, physics, chemistry or systems
  • Artefacts people use: fast libraries, benchmarks or well-cited papers

What's in it for you

  • $250k–$300k base
  • Work that goes straight into how frontier models are trained
  • A small, senior team where research and engineering are one job
  • Open to visa holders as well as US citizens and green card holders

Good to know

  • Full-time, on-site in San Francisco, 9-9-6
  • Process: first call with a founder → technical interview (a standalone problem, with an ML version in PyTorch) → work trial → offer

Does this sound like you? Apply now. If you're a match, we'll be in touch within 3 working days.

RnB Consultancy | Netherlands | 3604 AB Maarssen | KvK 71489703

Jobcon Logo Position Details

Posted:

Nov 12, 2026

Reference Number:

52e8a419

Employment:

Full-time

Salary:

$300,000 per year

City:

San Francisco

Job Origin:

ziprecruiter

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Job Description

Job Description

Researcher or engineer? This role wants both, in one person.

A profitable, seed-stage AI company in San Francisco creates long-horizon reinforcement learning environments and post-training data for leading AI labs in the US and abroad. Most data providers solve demand by adding people. This team treats post-training data as a research problem and scales it with processes that improve themselves. Demand for their data is bigger than what they can deliver today, so they're growing a small, very strong core team of researchers and engineers.

What you'll own

  • The full post-training loop: infrastructure, training runs and the data that goes into them
  • Long-horizon RL environments and tasks in many fields, from science to ML research itself
  • Scaling data generation through smarter, self-improving tooling, not more headcount
  • Judging which real-world tasks are worth building, because they matter to the labs and the economy

What you bring

  • Real depth in ML research (think post-training, RL, evals or interpretability) and serious engineering skills
  • You've post-trained models yourself and built the datasets for it
  • A good eye for data, or the research ability to build that eye fast
  • You read code fast and solve problems quickly in PyTorch and ML pipelines
  • Curiosity that shows: papers, side projects, open source contributions or writing
  • Roughly 3–7 years of experience

Bonus points

  • Both published research and things you actually shipped
  • Domain depth next to ML, such as neuroscience, physics, chemistry or systems
  • Artefacts people use: fast libraries, benchmarks or well-cited papers

What's in it for you

  • $250k–$300k base
  • Work that goes straight into how frontier models are trained
  • A small, senior team where research and engineering are one job
  • Open to visa holders as well as US citizens and green card holders

Good to know

  • Full-time, on-site in San Francisco, 9-9-6
  • Process: first call with a founder → technical interview (a standalone problem, with an ML version in PyTorch) → work trial → offer

Does this sound like you? Apply now. If you're a match, we'll be in touch within 3 working days.

RnB Consultancy | Netherlands | 3604 AB Maarssen | KvK 71489703

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