Engineering Manager, Applied AI

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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Salary

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401(k) match

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Market context

Median wage (BLS OEWS)

$111,944 national median

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.

Schedule

Shift type

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Weekend work

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Application

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Assessment

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Deadline

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Where they hire

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About this role

Engineering Manager, Applied AI San Francisco, California, United States, New York City About Mercor Mercor's mission is to organize human intelligence to power the AI economy. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development. Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $3 million a day. Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You'll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices. About the Role We're hiring Engineering Managers to lead teams within our Applied AI organization. Applied AI builds systems that directly improve model quality, including evaluation infrastructure, annotation products, and emerging multimodal capabilities. You'll lead a team of engineers, partner with product and research, and help define how Mercor stays at the frontier of AI. You will also build partnerships with leading AI labs and directly contribute to improving the quality of frontier models through data, evaluation, and systems. This role requires high ownership and abstraction: setting direction, driving outcomes, and staying hands-on while leading. What

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