Product Manager, AI Data Platforms & Enterprise

mercor.com; San Francisco (CA); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Bi-annual bonus

Equity grant

Relocation bonus

Housing stipend

Meals stipend

Equinox membership

Laundry reimbursement

Wellness reimbursement

Health insurance

Job summary

Mercor is seeking a Product Manager to own a major product area and work directly with engineering and leadership to turn ambiguous problems into shipped products. You’ll balance long-term strategy with rapid execution, shaping the company’s trajectory and bottom line.

You’ll partner with expert annotators, customers, and internal operators to understand needs, own end-to-end lifecycles, write specs, build dashboards, and ship features quickly in a fast-paced AI data platform environment.

Qualifications

• 2+ years as a product manager or similar role.
• Experience in SWE, ML, or DS preferred.
• Own outcomes with strong accountability.
• Able to self-direct in ambiguous contexts.
• Strong connection of user needs to business strategy.
• Experience conducting user research and interviews.

Responsibilities

• Own major product area with autonomy from conception to sunsetting.
• Write specs and PRDs; build dashboards and small PRs.
• Collaborate with engineering, research, operations, and design.
• Turn ambiguous problems into shipped products.
• Balance long-term strategy with rapid execution.
• Make data-driven decisions to drive growth and health.

Skills

Product management

Ownership

Independent work

Technical fluency

Strategic vision

User research

Metrics-driven

Cross-functional collaboration

Job description

Mercor is seeking a Product Manager to own a major product area and work directly with engineering and leadership to turn ambiguous problems into shipped products. You’ll balance long-term strategy with rapid execution, shaping the company’s trajectory and bottom line.

You’ll partner with expert annotators, customers, and internal operators to understand needs, own end-to-end lifecycles, write specs, build dashboards, and ship features quickly in a fast-paced AI data platform environment.