About this role
As an Engagement Manager on Scale's Generative AI team, you'll be the face of Scale to the world's leading AI labs and model builders — the labs training the foundational LLM and agent capabilities defining the field.
You'll own these customer relationships end to end: translating what researchers need into the complex human-data programs our delivery teams execute, advocating for customer success internally, and earning Scale more work through precise, trustworthy follow-through. You'll work cross-functionally with Operations, ML, Engineering, and Finance to ensure the seamless delivery of Scale's GenAI products and services.
You won't run data pipelines yourself — you own the customer relationship, shape requirements into delivery outcomes, and partner closely with the teams who execute them. The ideal candidate is organized, execution-focused, and thrives on managing complexity. Precision across tracking, documentation, and customer follow-through is what builds trust and wins repeat work.
What you’ll do:
• Own end-to-end account management for assigned frontier-lab customers, from opportunity scoping through project kickoff to completion.
• Translate customer requirements into well-defined human-data programs run by Scale's internal delivery operations teams.
• Manage customer communications, action items, and follow-ups across multiple concurrent projects with strong attention to detail.
• Act as a consultative thought partner to Scale's customers, shaping their needs into clear, deliverable project outcomes.
• Monitor delivery against customer throughput and quality standards, proactively flagging risks and escalating blockers with proposed solutions.
• Partner cross-functionally with operations, engineering, and planning teams to improve delivery efficiency and drive better customer outcomes.
What we’re looking for:
• 3+ years of work experience in consulting, technical program management, or project management.
• 2+ years of experience in B2B client-facing roles.
• Experience in a high-growth environment, working cross-functionally and wearing multiple hats.
• A technical background (education or professional experience with CS, Engineering, Economics, Mathematics, or another STEM field)
• Enough understanding of the ML training lifecycle to discuss use cases meaningfully with technical customers — or a clear ability to learn it quickly.
Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Directo