Product Manager: AI Environments & Frontier Tasks (Equity)

Mercor; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Bi-annual performance bonus structure

Generous equity grant vested over 4 yr

Up to $15k Relocation bonus

$10K housing bonus (0.5 miles from/off

$1.5K monthly meals stipend

Free Equinox membership

$200 monthly laundry reimbursement

$200 monthly personal wellness reimb

Job summary

Mercor is seeking a Product Manager for Environments in San Francisco. You will own a platform that turns a world into thousands of hard, verifiable training tasks, setting the quality bar labs rely on and enabling reuse across projects.

You will shape frontier training data and the next generation of agents through scalable task systems and clear success criteria. You will drive roadmap decisions, balance throughput, difficulty, and cost, and work closely with researchers and engineers to

Qualifications

• 3+ years as a product manager; SWE, ML, or DS background preferred.
• Strong ownership and accountability for outcomes.
• Ability to work independently in ambiguous contexts.
• Technical fluency and hands-on MVP capability valued.
• Strategic vision with ability to tie user needs to long-term direction.

Responsibilities

• Identify frontier capability gaps with frontier labs and translate into world, task, and verifier requirements.
• Build task generation systems turning a world into thousands of verifiable tasks.
• Set environment quality bars and implement checks for task difficulty and solvency.
• Create run-by-run feedback loops to monitor performance and push yield and difficulty.
• Develop a shared environment platform for scalable use across teams.
• Define roadmap and success criteria based on quality, throughput, and cost.

Skills

Product management

SWE experience

ML

DS

User research

Independent work

Job description

Mercor is seeking a Product Manager for Environments in San Francisco. You will own a platform that turns a world into thousands of hard, verifiable training tasks, setting the quality bar labs rely on and enabling reuse across projects.

You will shape frontier training data and the next generation of agents through scalable task systems and clear success criteria. You will drive roadmap decisions, balance throughput, difficulty, and cost, and work closely with researchers and engineers to