Research & Product Lead(AI Model Training) with Early Stage/ Startup/Founder Exp

Job Description

Job Description

Salary - $150,000 - $250,000

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