Scale AI’s Robotics team is enabling the future of physical AI by building the most advanced data collection and annotation programs in the industry. We are hiring a Director of Robotics Operations to lead these efforts end-to-end—from onsite lab operations to managing distributed contributor networks and downstream annotation workflows.
This role will manage a cross-functional operations team including site leads, independent data collectors, strategic project leads, engagement managers, and operational program managers. You’ll collaborate closely with Field Engineers (as key technical stakeholders) and cross-functional partners across Engineering, Product, and Go-To-Market.
If you’re an experienced operator who thrives in complexity, excels at building scalable systems, and wants to make a massive impact in a fast-moving space, we want to hear from you.
You will:
- Own and scale the full operations lifecycle for robotics data collection—from onsite physical setups to distributed contractor management and post-processing annotation pipelines.
- Lead a diverse team including Site Operations Leads, Strategic Project Leads, Engagement Managers, and Program Managers.
- Manage large networks of independent contributors across the globe to execute high-volume data collection at scale.
- Build and operationalize high-throughput, high-quality workflows across robotics programs—balancing speed, accuracy, and cost.
- Collaborate closely with Robotics Field Engineers, who are technical stakeholders responsible for hardware deployment and robotics integrations.
- Partner cross-functionally with Go-To-Market, Engineering, and Solutions teams to ensure successful execution of complex, customer-facing projects.
- Define and own key performance indicators (KPIs), including throughput, yield, cost per hour of data, and turnaround times.
- Solve operational bottlenecks and scale infrastructure to support rapid growth in customer demand and robotics deployments.
- Operate with urgency and clarity—driving execution while continuously improving workflows and systems.
You Have:
- 10+ years of experience in operations, logistics, robotics, or related fields, with a proven track record leading large, cross-functional teams.
- Demonstrated ability to manage and scale hybrid workforces—both full-time staff and distributed independent contractors.
- Experience building and running on-site physical operations (labs, field sites, or hardware-intensive environments).
- Proven success in high-complexity program execution and cross-functional collaboration.
- Experience managing highly technical operational workflows with both hardware and software in the loop.
- Technical fluency and a data-driven mindset; comfort working with SQL or Python is a strong plus.
- Experience operating in international markets, especially LATAM, including field deployments, compliance, and vendor management.
- Strong systems thinking, process design, and problem-solving skills.
- High operational rigor and a drive for continuous improvement.
- A track record of operational output excellence
Nice to Have:
- Experience in robotics, AV testing, or large-scale data annotation programs.
- Familiarity with fleet management, compliance frameworks, or automation workflows.
- Experience optimizing a global workforce with onshore and offshore operations.
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 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 that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information.
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Scale accelerates the development of AI applications by helping machine learning teams generate high-quality ground truth data. Our advanced LiDAR, image, video and NLP annotation APIs allow machine learning teams at companies like OpenAI, Lyft, Pinterest, and Airbnb focus on building differentiated models vs. labeling data.
