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Research & Product Lead

San Francisco, CA, USA

full time

on-site

Operations

$150,000 - $250,000

Competetive Equity

About This Role

Our Client is the only AI research lab exclusively focused on video data. Video already accounts for 80% of internet traffic and has become the dominant medium for creativity, communication, gaming, AR/VR, and robotics. Unlocking the ability to truly model video requires one thing above all else: high-quality training data. That is what Sieve builds. They combine exabyte-scale video infrastructure, novel video understanding techniques, and dozens of diverse data sources to create datasets that push the frontier of video modeling. They partner with top AI labs and did multiple millions in revenue last quarter alone as a team of just 15 people. Series A raised from Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.

About the Role

Our Client is hiring a Research & Product Lead to be a high-leverage generalist operator across the company. The role combines deep technical fluency with strong relationship skills, managing Sieve's most important customer accounts, driving cross-functional execution, and contributing wherever the company needs leverage. It sits at the intersection of product, applied research, customer engagement, and operations. You will be equally comfortable in a technical deep-dive as you are shaping roadmap priorities, navigating a commercial conversation, or building out scalable internal systems.

This role exists because Sieve's customer base comprises the most technically demanding organizations in the world, and the team is scaling fast. Managing those relationships and the operations behind them requires someone who can operate as a peer with the engineers and researchers they work with, while also building the systems that let the company scale.

The team is open to two candidate profiles:

• Senior track: experienced operators with existing AI lab relationships or a background at a human data company (Scale, Surge, Sapien, Mercor, Invisible, Toloka, Snorkel, Defined.ai, or similar)
• Generalist track: 1-2 years out of consulting (MBB or top tier), banking, or as an APM at an AI company, paired with an engineering degree and demonstrable technical curiosity

Across both tracks, the universal filter is high curiosity and high EQ.

What You'll Own

• Build and manage relationships with frontier AI labs and highly technical customers
• Translate customer needs into internal product and research priorities
• Operate as a strategic partner to both external customers and internal technical teams
• Drive cross-functional execution across research, product, operations, and partnerships
• Help identify operational bottlenecks and implement scalable systems and processes
• Support high-priority strategic initiatives across the company
• Work closely with researchers, engineers, and leadership on ambiguous, fast-moving projects
• Navigate technical conversations around datasets, model performance, infrastructure, and AI workflows
• Help shape how Sieve scales customer engagement and internal operations as the company grows
• Contribute wherever needed as a high-leverage generalist operator

Requirements

Must-Have

• Excellent general problem solving skills
• Bachelor's degree in computer science (or equivalent technical degree)
• Strong understanding of ML and AI workflows, particularly around data pipelines and model training
• Enough technical depth to hold substantive conversations with engineers and researchers at frontier AI labs
• Familiarity with how data quality, pipeline architecture, and dataset composition affect model training outcomes
• Excellent written and verbal communication that commands credibility with senior technical stakeholders
• Comfort translating between engineering and business audiences fluently
• High curiosity and high EQ
• Scrappy and able to pick things up on the job in a fast-moving startup environment
• In-person at Sieve SF HQ 5 days a week

Nice-to-Have

• Senior track: existing relationships at AI labs or frontier model companies (highest-signal background for the senior track)
• Senior track: background at a human data company (Scale, Surge, Sapien, Mercor, Invisible, Toloka, Snorkel, Defined.ai, Datasaur)
• Generalist track: engineering degree paired with 1-2 years at MBB, top consulting, banking, or APM at an AI company
• Background in video, media, or content-related technologies
• Prior early-stage startup experience, especially as an early hire who saw a customer-facing function get built from zero
• Experience in product, technical operations, or a customer-facing technical role