Six Figure Work

Member of Technical Staff, Enterprise Evals Platform

Mercor

Company websitemercor.com (Mercor, opens in new tab)

Base salary $220K  to $425K

Employer-published annual base salary, USD. Advertised base range in San Francisco, CA

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  • LocationSan Francisco, CA
  • WorkplaceOn-site
  • Status at last checkSource accepting applications when checked
  • Last checked (2 h ago) · observed since

About this job

About Mercor

Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents.

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

Enterprise agents are complex systems, and they only pay off when their work is reliable and economically viable. Evaluation is how you get both: checking correctness is the obvious case, and routing is the subtler one, since choosing a model against cost, latency, and quality requires quality to be measurable at all. Knowing where the bar sits is the hard part. You decompose real work, take the standard from the practitioners who hold it, and encode it so an agent cannot shortcut it.

You will apply what Mercor has learned building benchmarks with domain experts, and devise new methods, so that evals and rubrics keep improving and so do the agents measured against them.

That work only scales with a platform behind it. This is a platform engineering role with good depth of understanding in evals. You will build the verifiers, the environments agents are measured in, and the grading infrastructure that runs at scale, abstracted across customers, domains, and tasks so that every run becomes evidence the next agent inherits instead of starting over.

Read more about how we think about this: Agent Eval Systems

Responsibilities

  • Define golden sets: decompose real tasks and encode the expert quality bar.

  • Build verifiers over agent trajectories and outputs, calibrated and hard to game.

  • Build the eval platform that runs offline environments, task suites, and grading at scale.

  • Run loss analysis over production trajectories and turn failure modes into regression tests.

  • Run the optimization loop across models, prompts, skills, and harnesses.

  • Own the rollout gates that decide whether an agent change ships.

  • Partner with the Enterprise Platform team and the Applied AI engineers embedded with customers.

What We're Looking For

  • Professional, academic, or research experience in agent engineering and evaluation, including how agent runtimes and harnesses produce a trajectory and where it fails.

  • Bachelor’s Degree in Computer Science or a related technical degree such as Electrical Engineering, Physics, Mathematics, Computer Engineering, Information Systems or Statistics

  • 1–5 years in industry level software engineering

  • Experience building evaluation suites for LLM or agent systems, and familiarity with how benchmarks such as terminal-bench, tau-bench, and APEX are constructed and where they get gamed.

  • Judgment about task and rubric design: turning a fuzzy notion of quality into something measurable, with agent or model improvements to show for it.

  • Strong software engineering fundamentals, and the ability to work independently on ambiguous, loosely specified problems.

  • Bonus: experience with Harbor environments and RL environments.

Why Mercor

  • Impact: No agent reaches an enterprise customer without clearing the bar you set.

  • Learning: Eval work spanning frontier model measurement and live enterprise deployments, on production trajectories few teams get to see.

  • Growth: Research and systems in one role, with fast paths to owning the eval system end to end.

Benefits

  • Up to $15k relocation bonus

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

  • $1.5K monthly stipend for meals

  • Generous equity grant vested over 4 years

  • Free Equinox membership

  • $200 monthly laundry reimbursement

  • $200 monthly personal wellness reimbursement

  • Health, Dental, Vision insurance

Source: Mercor on Ashby · View original posting (opens in new tab)

Pay in context

This role's base floor ($220,000) is above 79% of the 5,063 Software Engineering roles in California listed on this site; 83 others list the same floor. Their median floor is $176,600; the middle half runs from $149,365 to $204,000.

Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 8, 2026.

This range next to 6 other live Mercor roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live Mercor roles with the nearest advertised base floor
RolePublished base
Member of Technical Staff, Enterprise Evals Platform (this listing)$220K - $425K
Software Engineer, Systems & Platform Applied AI$220K - $500K
Brand Design Lead$200K - $300K
Head of Operations Planning$200K - $250K
Research Engineer – Benchmarking$200K - $500K
AI Infrastructure Engineer$200K - $400K
Research Scientist, APEX Benchmarks$200K - $500K

Same $100K to $400K scale as every card. All Mercor roles · How to read the bar

Observed changes

  1. Began meeting the published-salary criteria
  2. First observed on the employer's board
Observed since
Employer-stated posting date
2026-08-15
Where this pay comes from

Location as the employer wrote it: San Francisco

USD 220,000 – 425,000 · 1 YEAR · Salary

Method
Structured pay field published by the employer
Checked
Rule set
us-base-v2

The employer's job board publishes this pay as a dedicated data field. We read the field directly; no interpretation was needed.

What we verified

  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.

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