Experience: 5+ years
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Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:
$205,600—$257,000 USD
Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world's most important decisions.
Coding is one of Scale's strongest and fastest-moving domains. We built SWE-Bench Pro, a contamination-resistant benchmark of 1,865 long-horizon software engineering tasks across 41 repositories — including a first-of-its-kind private set drawn from proprietary startup codebases — which cut frontier model scores from over 70% on SWE-Bench Verified to roughly 23%, and became a reference point for how the industry measures coding agents. We then extended that foundation with SWE Atlas, an evaluation suite spanning Codebase QnA, Test Writing, and Refactoring, which measures the full engineering loop rather than issue resolution alone. And we are among the largest external contributors to the FrontierBench (Formerly Terminal-Bench) lineage, contributing more tasks than any other single organization to the launch set.
We're looking for a Senior AI Product Manager to own and scale this Coding portfolio from here. In this role, you will define the strategy, roadmap, and operational excellence of Scale's coding data products, RL environments, and agentic coding evaluations. You will work across AI Product Management, ML Researchers, Engineering, Operations, and Go-To-Market teams to turn our benchmark credibility into a durable, revenue-generating product line that leading labs depend on to train the next generation of software engineering agents.
You will serve as the product owner for coding initiatives, driving task design, environment infrastructure, expert contributor quality, customer adoption, and business impact. You will work directly with leading AI labs and enterprise customers, representing Scale as a thought partner in how coding models are trained and measured.
The ideal candidate combines strong product judgment, hands-on technical depth in software engineering, operational rigor, and customer-facing experience, with a passion for turning emerging model capabilities into scalable data products.
You Will
Ideally, You'd Have
Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
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