Strategic Project Lead, Robotics

Scale AI
San Francisco, CAPosted 7 April 2026

Job Description

Scale’s Robotics business unit is currently seeing historic levels of growth. As a Strategic Projects Lead (SPL) for the Data Collection team, you will lead initiatives that will drive $XXM+ in new revenue for the business. This is a demanding role, and as an SPL, you should be prepared to wear many hats across all dimensions of Operations. The ideal SPL should have a strong entrepreneurial mindset, be comfortable getting into the weeds, and be excited about intense, impactful work that leads to accelerated career progression. You will: Serve as the full owner of our most visible and high impact customer and internal collection projects, making decisions that directly impact data quality, operational efficiency, revenue, and margins Understand customer requirements and design collection specifications best suited to improving model performance based on customer needs Build out project timelines and pipeline infrastructure to ensure quality and efficiency Train, coach, and manage dynamic and global teams of operators and collectors Build analytics and reports to make data-driven decisions Functionally lead a team of Operations Program Managers and Associates that support the execution of the project, define and assign tasks, monitor progress Partner with diverse stakeholders (Engineering + Product + Finance + Go-to-Market) to work on problems that will drive advancements for the largest Robotics models (VLAs/VLMs) in the world Give regular progress updates to Scale’s executive team Ideally, you’d have: Strong technical background, combined with a business-oriented mindset (a degree in engineering or computer science is ideal + prior exposure to driving business outcomes). 3+ years of experience leading a project team, developing product or operational processes, or launching new operations. Excellent problem-solving capabilities (experience working on operational challenges is a plus) - ability to come up with creative solutions to complex, ambiguous operational problems Entrepreneurial experience and mindset - you are excited about building things from scratch and are able to identify issues and execute quickly Nice to haves: Hands-on experience in Robotics, AI, and/or Computer Vision Experience working with global teams on different timezones SQL proficiency 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, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $152,000 $190,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications t ... (truncated, view full listing at source)
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