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Mercor
Mercor

Machine Learning Engineer

RoleMachine Learning
LevelMid Level
LocationSan Francisco, Canada, United States
WorkOn-site
TypeFull-time
Posted2 months ago
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Required skills

Python

Machine Learning

ABOUT MERCOR

Mercor is at the intersection of labor markets and AI research. 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 $2 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 new San Francisco headquarters.

About the Role:

As a Machine Learning Engineer at Mercor, you’ll operate at the intersection of backend engineering and applied machine learning. ML Engineers at Mercor are generalists first, shipping production systems that power performance prediction, search, recommendation, and fraud detection while also bringing statistical and modeling rigor where it matters. The work spans everything from building APIs and infrastructure to training and deploying models, always tied closely to core product outcomes. You’ll collaborate with product engineers and operations to deliver systems that directly impact how companies source talent and how candidates find opportunities

You will:

  • Research, train, and productionize ML models for engagement prediction, scoring, search

  • Build backend infrastructure and APIs to serve ML models reliably at scale.

  • Run experiments, analyze results, and iterate quickly to improve both models and product performance.

  • Work cross-functionally with Operations and Product to translate business needs into model-driven solutions.

  • Wear many hats: from backend engineer to applied ML practitioner to product problem-solver.

What We’re Looking For:

  • Strong backend engineering skills (ex. Python/Django or similar) plus a solid foundation in applied ML and statistics.

  • Proven experience shipping production systems or ML-driven products end-to-end.

  • High ownership and comfort operating in ambiguous, fast-changing environments.

  • Generalist mindset: willing to flex between backend, modeling, data pipelines, and product problem-solving.

Why Mercor

  • Impact: Your work powers how the world’s leading AI labs train and test their models.

  • Learning: Get early insights into frontier model capabilities months before the market.

  • Growth: Work on both infrastructure and research-adjacent projects with fast paths to ownership.

Benefits:

  • Generous equity grant vested over 4 years

  • A $20K relocation bonus (if moving to the Bay Area)

  • A $10K housing bonus (if you live within 0.5 miles of our office)

  • A $1K monthly stipend for meals

  • Free Equinox membership

  • Health insurance

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About Mercor

Mercor

Mercor

Seed

Mercor is an AI-powered platform that connects companies with vetted software engineers and technical talent through automated screening and matching processes.

1-50

Employees

San Francisco

Headquarters

Reviews

10 reviews

4.0

10 reviews

Work-life balance

3.2

Compensation

3.8

Culture

4.3

Career

3.5

Management

4.2

72%

Recommend to a friend

Pros

Supportive and approachable management

Great team culture and collaborative environment

Good benefits and flexible work options

Cons

Heavy workload and frequent overtime

Communication issues and miscommunication

Non-competitive pay and limited career progression

Salary Ranges

6 data points

Mid/L4

Mid/L4 · Machine Learning Engineer

1 reports

$210,126

total per year

Base

$161,637

Stock

-

Bonus

-

$210,126

$210,126

Interview experience

3 interviews

Difficulty

3.0

/ 5

Offer rate

67%

Experience

Positive 0%

Neutral 67%

Negative 33%

Interview process

1

Application Review

2

AI Interview Screen

3

Technical Assessment

4

Final Review

5

Offer

Common questions

Domain Expertise

Behavioral/STAR

Industry Knowledge

Leadership Experience

Problem Solving