Strategic Project Lead - AI Data Startup

Mannelly Recruitment•San Francisco, CA

4d•Onsite

About The Position

A fast-growing AI data startup is hiring ten Strategic Project Leads across STEM domains to serve leading AI labs seeking data in a broader range of scientific fields. The role acts as an in-house subject-matter expert, defining high-quality data and designing dataset specifications and evaluation criteria that shape how frontier models are trained, tested, and improved. The Project Lead recruits, leads, and coordinates teams of specialized expert contributors; owns critical projects from scoping through delivery; partners with leading AI organizations; and contributes to operational initiatives across the business. This is a high-ownership, fast-moving, onsite position in San Francisco for a scientist moving from research into building. Compensation includes a competitive base salary, on-target earnings that regularly reach two to three times base, and equity. The role requires working onsite in San Francisco five days a week, plus a half day on Sunday, which may be remote or onsite. Visa transfers, including OPT or H1B transfers, are welcome; new visa sponsorship is not available.

Requirements

PhD (completed or ABD) in biology, chemistry, mathematics, statistics, or a related STEM field, or equivalent distinction such as an IOI, IMO, or USAPhO medal; ICPC or USACO finalist; or Putnam top 500 finisher.
0 to 8 years of experience as an expert in a STEM field.
Experience with Python, R, or another language used for data analysis.
Deep scientific or quantitative research background, with the ability to discuss the work credibly and uphold high standards for datasets.
Entrepreneurial, high-ownership mindset and drive to work in a fast-moving, high-stakes environment.
Ability to work onsite in San Francisco five days per week, plus a half day on Sunday, remotely or onsite.

Nice To Haves

Internship or fellowship at a highly regarded company or research lab.
Degree from a top-20 STEM program.
Familiarity with how large language models are trained, fine-tuned, or evaluated.

Responsibilities

Act as the in-house subject-matter expert for a STEM domain.
Define standards for high-quality data and design dataset specifications and evaluation criteria.
Recruit, lead, and coordinate teams of specialized expert contributors.
Own critical projects from scoping through delivery.
Partner with leading AI organizations.
Contribute to operational initiatives across the business.