Data Product Operations Lead

Mannelly Recruitment•San Francisco, CA

2d•Onsite

About The Position

A fast-growing AI data startup is hiring a Data Product Operations Lead to run projects supporting its data platform, which is in rising demand from major technology companies and top AI research labs. More than half of the role involves leading projects from start to finish: setting requirements, arranging staffing and resources, and delivering finished datasets to customers. The role also involves improving data through research, working with voice actor contributors, and partnering with engineering and machine learning teams. The Lead will design, monitor, and scale data pipelines from initial prototype through full production volume, using throughput, quality, and cost metrics to identify and resolve bottlenecks. About 10 percent of the role involves working with researchers at frontier AI labs on deliveries. This is a full-time, onsite position in San Francisco. The company offers a competitive salary plus equity. Relocation support and new visa sponsorship are not available; visa transfers, including OPT or H1B transfers, are welcome.

Requirements

At least 1 year of experience in a high-intensity setting, such as top-tier consulting, strategy and operations at a leading marketplace company, an early-stage startup, or a human data company.
Experience as a management consultant, strategy and operations lead, or product operations lead.
Experience owning a project or pipeline end to end, from early prototype through production scaling.
Experience leading cross-functional workstreams across operations, product, and engineering.
Good product sense and comfort working with engineers.
A scrappy, hardworking approach and an analytical mindset.
SQL skills or willingness to learn SQL on the job.
Bachelor’s degree required.

Nice To Haves

Degree from a top school or a STEM degree.
Customer-facing experience with technical stakeholders.
Human data or AI training data experience.
Audio or voice domain knowledge.

Responsibilities

Lead projects from start to finish, including setting requirements, arranging staffing and resources, and delivering completed datasets to customers.
Improve data through research and work with voice actor contributors.
Partner with engineering and machine learning teams.
Design, monitor, and scale data pipelines from prototype through full production volume.
Use throughput, quality, and cost metrics to identify and resolve bottlenecks.
Work with researchers at frontier AI labs on deliveries, representing about 10 percent of the role.