Research Engineer, Environment Scaling

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

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Salary

$350K-$850K From the posting source

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

436% above the BLS role benchmark for data and ml aggregate.

Posted salary is far from this role benchmark; treat it as low confidence.

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

Seniority

Mid From the posting source

Work mode

Remote From the posting source

In-office days

0 days From the posting source

Schedule

Shift type

Not verified

Weekend work

Not verified

Company

Equity

Offered From the posting source

Application

Cover letter

Not verified

Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Research Engineer, Environment Scaling Remote-Friendly (Travel Required) | San Francisco, CA About Anthropic Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Environment Scaling team is a team of researchers and engineers whose goal is to improve the intelligence of our public models for novel verticals and use cases. The team builds the training environments that fuel RL at scale. This is a unique role that combines executing directly on ML research, data operations, and project management to improve our models. You'll own the end-to-end process of creating RL environments for new capabilities: identifying high-value tasks, designing reward signals, managing vendor relationships, and measuring impact on model performance. Responsibilities: - Improve and execute our fine-tuning strategies for adapting Claude to new domains and tasks - Manage technical relationships with external data vendors, including evaluation of data quality and reward design - Collaborate with domain experts to design data pipelines and evaluations - Explore novel ways of creating RL environments for high value tasks - Develop and improve QA frameworks to catch reward hacking and ensure environment quality - Partner with other RL research teams and product teams to translate capability goals into training environments and evals You may be a good fit if you:

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