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Applied Machine Learning Engineer, Economist
Mercor
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About this role
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
As an Economist on the Marketplace team, you will bring economic theory and rigorous empirical methods to the core decision systems that govern how talent and opportunities meet on Mercor. You'll study and shape marketplace dynamics — matching efficiency, pricing, incentives, liquidity, and supply/demand balance — and turn those insights into mechanisms and metrics that directly affect fill rate, hiring speed, earnings, and revenue.
This is a high-impact, applied role at the intersection of economics, data science, and engineering. You'll help design the incentive structures and allocation mechanisms of a rapidly scaling two-sided labor market, and partner closely with ML, product, and engineering to put them into production.
WHAT YOU'LL OWN
- Marketplace mechanism design: pricing, incentives, and allocation rules that balance supply and demand
- Causal measurement of marketplace health — liquidity, match quality, fill rate, time-to-hire, and earnings
- Experimentation: A/B and marketplace/switchback experiments to evaluate interventions under interference
- Forecasting and modeling of supply, demand, and capacity across the talent network
- Economic framing of ranking, matching, and routing objectives, in partnership with ML and engineering
EXAMPLE PROBLEMS
- Design pricing and incentive mechanisms that improve liquidity without sacrificing quality or margin
- Quantify and mitigate marketplace failure modes: cold start, congestion, thinness, and supply/demand imbalance
- Measure the causal impact of matching and routing changes when market participants interfere with one another
- Build supply/demand forecasts that drive capacity planning and sourcing decisions
- Define the objective functions and guardrail metrics the marketplace optimizes toward
WHAT WE'RE LOOKING FOR
- Advanced degree (PhD or Master's) in Economics or a related quantitative field, or equivalent applied experience
- Strong foundation in microeconomics / market design and in causal inference and experimentation
- Proficiency with data and code (SQL plus Python or R) to run analyses end-to-end on real data
- Ability to translate economic theory into mechanisms and metrics that ship in a live product
- Clear communication of rigorous analysis to both technical and business audiences
NICE TO HAVE
- • Experience with marketplaces, pricing, ranking/matching, or two-sided platforms (labor, ads, ridesharing, etc.)
- • Familiarity with experimentation under interference (network or marketplace experiments)
- • Experience partnering with ML and engineering teams to productionize models or mechanisms
WHY THIS ROLE
Mercor is a two-sided marketplace at its core. This role owns the economic logic of that marketplace — the incentives, prices, and allocation rules that determine who gets matched, how fast, and at what value. Your work will shape fundamental marketplace outcomes across quality, speed, earnings, and revenue.
BENEFITS
- Bi-annual performance bonus structure
- Generous equity grant vested over 4 years
- Up to $15k Relocation bonus
- $10K housing bonus (if you live within 0.5 miles of our office)
- $1.5K monthly stipend for meals
- Free Equinox membership
- $200 monthly laundry reimbursement
- $200 monthly personal wellness reimbursement
- Health, Dental, Vision insurance
Salary insight
The midpoint of this range ($315k) is about 55% above the median disclosed salary for San Francisco roles listed on ForgeApply ($204k across 6,442 jobs).
See full Machine Learning Engineer salary data for San Francisco →
Based on live postings with disclosed pay on ForgeApply; refreshed daily. Not an estimate of this employer's offer.
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