Data Scientist, Marketplace Incentives
Company websitebuild.ai (Build AI, opens in new tab)
Base salary $180K to $280K
Employer-published annual base salary, USD. Advertised base range in San Francisco, CA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSan Francisco, CA
- WorkplaceOn-site
- Status at last checkSource accepting applications when checked
- Last checked (2 h ago) · observed since
About this job
About Build AI
Build AI is the data hyperscaler for Physical AI. We're vertically integrated across hardware, manufacturing, logistics, collection, and model training to scale the physical labor dataset orders of magnitude faster than anyone in the world.
Job Summary
This role exists to hillclimb the dataset objective: the ideal dataset, the objective function, the taxonomy, and the value of incremental data. You take that objective and maximize it: incentives, marketplace design, and collection behavior so the next hour we collect actually moves the score.
Key Responsibilities
Treat the Dataset & Quality objective / value function as the thing you optimize — not raw hours, not vanity volume
Design marketplace mechanics (task mix, targeting, bonuses, payouts, eligibility) so collectors produce high-value data
Run experiments: treatment assignment, holdouts, pay and bonus tests; keep the ones that hillclimb the objective and kill the rest
Measure whether incremental collection is improving the dataset under the value function, and report that in language ops can act on
Work with software to ship incentive and payout changes into the collection product (not a spreadsheet that never lands)
Watch for Goodhart: collectors optimizing the proxy instead of the objective, and close those holes
You may be a good fit if you have (Must-have qualifications)
Quantitative: you can take someone else’s objective function and optimize against it
Comfortable designing and reading experiments (assignment, holdouts, power, leakage)
Comfortable with messy field / collection data
You like iteration: small changes, measured against the objective, shipped again
Strong candidates may also have experience with (Nice-to-have qualifications)
Experience with marketplaces, incentives, pricing, or growth experimentation (gig, two-sided, or similar)
Experience with payouts, bonuses, or pay systems that moved real money
You have shipped experiment results into a product, not only a notebook
Benefits
Competitive pay
Medical, dental, and vision packages with generous premium coverage
$500 per month credit for waiving medical benefits
Housing subsidy of $2k per month for those living within walking distance of the office
Relocation support for those moving to San Francisco (Financial District) or Shenzhen (Nanshan)
Various wellness benefits covering fitness, mental health, and more
Daily lunch and dinner in our office
Unlimited compute budget subject to ROI justification
Unlimited Codex and Claude credits
Travel
How we're different
Build believes in the Bitter Lesson. By taking a general approach of learning from humans, our addressable market is all physical labor.
We are a fully in-person team in San Francisco (Financial District) and Shenzhen (Nanshan), and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both and work across disciplines as needed.
Build AI is an equal opportunity employer. We review every application. If you do not meet every bullet, still apply. Questions: [email protected]
Source: Build AI on Ashby · View original posting (opens in new tab)
This listingData Scientist, Marketplace Incentives$180K to $280K
Software Engineer, Scaling$180K to $300K
Software Engineer, Generalist$180K to $300K
Software Engineer, Data Visualization$180K to $300K
Head of Data Compliance$160K to $250K
ML Engineer, Inference Optimization$200K to $320K
Product Lead$200K to $300K
Chart as a table
| Role | Published base |
|---|---|
| Data Scientist, Marketplace Incentives (this listing) | $180K - $280K |
| Software Engineer, Scaling | $180K - $300K |
| Software Engineer, Generalist | $180K - $300K |
| Software Engineer, Data Visualization | $180K - $300K |
| Head of Data Compliance | $160K - $250K |
| ML Engineer, Inference Optimization | $200K - $320K |
| Product Lead | $200K - $300K |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2026-08-30
Where this pay comes from
Location as the employer wrote it: San Francisco
USD 180,000 – 280,000 · 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.
