SECTION I · THE BRIEF
Brief #80197Updated 22 AUG 2026SAN FRANCISCO, CAYc
Employbl Company Profile

Member of Technical Staff, Reinforcement Learning

Outerport is hiring a Member of Technical Staff, Reinforcement Learning in San Francisco, CA. Full brief — comp band, interview process, and hiring team — available to Employbl members.

Location
San Francisco, CA
Company size
1–10
Posted
4d ago
Via
Yc
Section II · Premium ProfileMembers only
  • 01Comp band & equity packageLocked
  • 02Seniority & experience requirementsLocked
  • 03Interview process & rubricLocked
  • 04Hiring manager & team contextLocked
  • 05Growth trajectory in this roleLocked
  • 06Offer & decision timelineLocked

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Member of Technical Staff, Reinforcement Learning · Outerport

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Job title
Member of Technical Staff, Reinforcement Learning
Job location
San Francisco, CA, US / Tokyo, JP
Job description
We’re looking for candidates with experience building reinforcement learning-based LLM training pipelines. As part of our founding team you may: * Train reinforcement learning-based LLMs to solve tasks in the domain of materials science, chemical engineering, and engineering science * Integrate simulation tools and real hardware to collect data * Work with and source data from vendors * Evaluate, test, and deploy models Qualifications (none of these are hard requirements) * Industry experience or projects working on hard problems in machine learning (with Python / PyTorch) * Being scrappy (getting things done, over theoretical soundness) * Publication record in venues like ICLR, NeurIPS, ICML, and others * Good visual taste / an appreciation for aesthetics * A reputation for having an “engineering mindset” * Strong communication skills * Experience working with various engineering simulation tools (e.g. CAE, EDA tools) * Interest in manufacturing, engineering, EPC, semiconductors, materials science
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Where this role is based

San Francisco, CA

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Outerport headquarters

Company size

110 employees

Founded

2024

Total raised

$500,000

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Funding rounds

  • Pre Seed$500K