Member of Technical Staff - Research

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

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401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Staff Plus From the posting source checked Jun 20, 2026

Work mode

Onsite From the posting source checked Jun 20, 2026

In-office days

5 days From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Company stage

Seed From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Member of Technical Staff - Research San Francisco | OnSite About Polymath Polymath is an applied research lab focused on advancing long-horizon agent capabilities through reinforcement learning. We design and scale simulation environments where agents learn to operate safely and autonomously. We work with the world's leading model labs to push the frontier of agent capabilities. Polymath is backed by Base10, Founders Future, Y Combinator, and other incredible investors & angels. We've raised an $8M seed, and are growing out our founding team. About the role We're hiring a Member of Technical Staff - Research to help advance the frontier of autonomous agents. You'll work on core research problems in long-horizon evaluation, agent post-training, and environment design, with a focus on understanding where current models fail and how to improve them. As a member of the founding team, you should expect to wear multiple hats: building benchmarks, creating environments, writing production code, and running rigorous experiments. We're looking for people who are excited by hard open-ended problems and want to operate at the intersection of research and engineering. Examples of projects you could work on include: - Developing an advanced environment simulation engine for training & evaluating autonomous AI agents - Investigating failure modes of frontier models - Creating rigorous benchmarks that evaluate how well frontier agents perform on complex, realistic tasks requiring long-horizon reasoning and tool use in dynamic environments - Post-training agents in complex simulation environments - Publishing research You'll be a good fit if you: - Have

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