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Jobs/San Francisco/Training: ML Framework Engineer
San Francisco, CA

Training: ML Framework Engineer

About the Team Training Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we’re building a unified, modular runtime that meets researchers wh

Company
OpenAI
Compensation
$205K - $445K
Schedule
Full-Time
Role overview

What this role actually needs.

About the Team Training Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we’re building a unified, modular runtime that meets researchers wh Responsibilities: - Apply the latest techniques in our internal training framework to achieve impressive hardware efficiency for our training runs - Profile and optimize our training framework - Work with researchers to enable them to develop the next generation of models - Have run small scale ML experiments - Love figuring out how systems work and continuously come up with ideas for how to make them faster while minimizing complexity and maintenance burden - Have strong software engineering skills and are proficient in Python Company context: OpenAI builds frontier AI systems, research infrastructure, and applied products for developers, enterprises, and global users.

Responsibilities

Day-to-day expectations

OpenAI lists these responsibilities for the Training: ML Framework Engineer role.

  • Apply the latest techniques in our internal training framework to achieve impressive hardware efficiency for our training runs
  • Profile and optimize our training framework
  • Work with researchers to enable them to develop the next generation of models
  • Have run small scale ML experiments
  • Love figuring out how systems work and continuously come up with ideas for how to make them faster while minimizing complexity and maintenance burden
  • Have strong software engineering skills and are proficient in Python
UpJobz market context

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Training: ML Framework Engineer is framed against UpJobz source checks, country scope, compensation visibility, and work-authorization signals so candidates can make a faster go/no-go decision.

United States tech market

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Compensation read

$205K - $445K is visible before the click, so candidates can compare the role against local market expectations before applying.

Work authorization read

Current extracted signal: United States residents. UpJobz treats this as a search signal, not legal advice, and links visa-sensitive roles back to the relevant visa hub where possible.

Location read

On-site roles in San Francisco should be compared against commute, local salary bands, and nearby employer demand.

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Subscriber playbook

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Next moves

  • Tailor your resume around ai and machine-learning instead of sending a generic application.
  • Use the first two bullets of your application to connect your background directly to training: ml framework engineer is a high-signal on-site role in san francisco, and it is most realistic for united states residents.
  • Open the role quickly if it fits and bookmark three similar jobs before you leave the page.

Interview themes

Artificial IntelligenceOn-siteaimachine-learningresearchpython

Watchouts

  • $205K - $445K is visible, so calibrate your application around the posted range.
  • Use united states residents as part of your positioning so the recruiter does not have to infer it.
  • Show concrete examples of succeeding in on-site environments.
Role signals

Keywords to match against your background

Use these terms to decide whether your resume, portfolio, and recent projects line up with the role.

aimachine-learningresearchpythonawssecurityplatformobservabilityapillminfrastructure
Next step

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Source: jobs.ashbyhq.com · Source ID: d8794980-1d3f-4d82-8b48-811449b6c492 · Confidence: 97/100 · Last checked: May 7, 2026

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