Member of Technical Staff

About the Company

We're partnering with a stealth AI infrastructure company building the data layer for frontier AI development. Founded by industry veterans from a top frontier AI lab and an AI infrastructure decacorn, the company is already working with leading AI labs across computer use, finance, multimodal generation, and enterprise productivity. Its long-term vision is to become the trusted infrastructure partner helping frontier models move beyond answering questions to reliably performing high-value work across the economy.

Company Snapshot

• $30M funded AI/data company founded in 2025.
• Founding and leadership team includes veterans from frontier AI labs, Meta, Scale AI, and Anthropic.
• Already working with top AI labs on critical capability areas while still in stealth.
• Building across computer use, finance, multimodal generation, and enterprise productivity.
• Approximately 30 employees, with the opportunity to join as one of the first dedicated research hires.

Why You Should Join

• Shape how frontier AI models are evaluated and improved.
• Work directly with leading AI labs on high-impact capability areas.
• Join an exceptionally research-heavy team with backgrounds from Meta, Anthropic, Scale AI, and frontier labs.
• Own benchmark, evaluation, and data-quality strategy from an early stage.
• Work at the intersection of AI research, data infrastructure, and frontier model development.

About the Role

You'll join as a Member of Technical Staff focused on AI/ML research, helping define how frontier models are evaluated and improved. You'll design benchmarks and evaluations, build high-quality datasets, conduct quantitative research, and collaborate closely with AI researchers and engineers.

Qualifications

• 6–10 years of AI/ML research experience across academia and industry.
• Published research at ICML, NeurIPS, ACL, or equivalent as a top/lead author.
• Industry research experience at an AI lab or AI infrastructure company such as Google DeepMind, Anthropic, OpenAI, or Scale AI.
• Experience designing LLM benchmarks, evaluations, or datasets.
• PhD in ML, CS, Computer Vision, Statistics, or quantitative science from a top-tier program preferred.
• Strong Python/PyTorch engineering fluency.

Pay range and compensation package

• Compensation: $250K–$350K Base + Equity
• Location: New York or San Francisco
• Work Model: Onsite
• Visa: Sponsorship available.