Head of Dataset Design & Quality for Scalable AI

Build AI; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Competitive pay

Medical, dental, and vision

Housing subsidy

Relocation support

Wellness benefits

Daily lunch

Unlimited compute budget

Codex and Claude credits

Travel

Job summary

Build AI in San Francisco is seeking a data-centric quant researcher to define dataset strategy for physical labor tasks, design taxonomy, and the value function for incremental data. You will shape how we collect, label, and evaluate data to maximize informational gain.

You will collaborate with engineers and researchers to scale collection across real-world environments, set quality standards, and contribute across disciplines in a hands-on, in-person team.

Qualifications

• Quant background in statistics, decision science, or similar.
• Experience with dataset design, collection strategy, or large-scale data programs.
• Ability to argue about scaling vs fidelity with numbers.
• Familiarity with in-the-wild collection, video, or pose data (nice-to-have).

Responsibilities

• Define the ideal dataset for solving physical labor and the objective function on current data.
• Design taxonomy, golden sets, acceptance criteria, and audit for measurable quality.
• Create value function for incremental data and determine next data points.
• Translate strategy into collection plans, standards, and vendor execution.
• Avoid unnecessary process that reduces throughput and information gain.
• Align dataset decisions with model capability metrics and scorecards.
• Collaborate with Evals Lead to ensure dataset decisions inform models.

Skills

Quantitative background

Dataset design

Decision science

Advocating scaling vs fidelity

Job description

Build AI in San Francisco is seeking a data-centric quant researcher to define dataset strategy for physical labor tasks, design taxonomy, and the value function for incremental data. You will shape how we collect, label, and evaluate data to maximize informational gain.

You will collaborate with engineers and researchers to scale collection across real-world environments, set quality standards, and contribute across disciplines in a hands-on, in-person team.