Strategic Projects Lead

About Rise Data Labs

Rise Data Labs powers the training and evaluation of frontier AI models with elite, US-based domain experts paired with automation that scales quality. AI labs and enterprise teams rely on us for high-fidelity human data across healthcare, law, finance, engineering, and more.

About the role

As a Strategic Projects Lead (SPL), you'll own our most important customer projects end to end. You'll be the main point of contact for AI lab customers, turn their research goals into clear data specifications, and lead teams of expert contributors to deliver high-quality datasets on tight timelines. This is a high-ownership role at the center of our business: part project lead, part operator, part product thinker.

What you'll do

• Own projects end to end: scope, plan, execute, iterate, and deliver datasets for leading AI labs and enterprise customers.
• Be the customer's main point of contact: run check-ins, share progress, manage expectations, and surface risks early.
• Translate research needs into specs: write clear guidelines, rubrics, and task designs that shape how models are trained and evaluated.
• Lead expert teams: recruit, onboard, and manage domain specialists (PhDs, engineers, clinicians, lawyers, analysts) to produce work at scale.
• Own quality: design QA workflows, review samples, track metrics, and continuously raise the bar on data integrity.
• Improve how we operate: build playbooks, tooling requests, and processes that make the next project faster and better.

What we're looking for

• 2+ years of experience in project or program management, consulting, operations, or a similarly high-ownership role.
• Exceptional written and verbal communication; comfortable working directly with technical customers.
• Proven ability to turn ambiguous problems into structured, executable plans.
• Strong attention to detail and a high bar for quality.
• Comfort in fast-paced, startup environments with shifting priorities.
• Bachelor's degree or equivalent practical experience.

Nice to have

• Experience at an AI/ML company or with data annotation, RLHF, or model evaluation projects.
• Background managing distributed or freelance teams.
• Familiarity with LLMs and a genuine interest in how they are trained and evaluated.