At Scale, we are developing the data infrastructure that powers reliable AI systems in the physical world. The Industrial Partnerships team is a critical function for scaling high-quality data collection through a global network of external partners, expanding our capacity and geographic reach. Joining this team offers a unique opportunity to build complex operations and lead cross-functional coordination to launch new partners and transform that network into a world-class operational engine.
These roles are responsible for identifying and signing new partner businesses, and coordinating day-to-day operations with existing partners, including performance tracking and ongoing support.
You will:
- Identify and engage prospective partner businesses and manage the process through to signed agreement
- Coordinate day-to-day operations with signed partners including onboarding and ongoing support
- Track partner performance and data collection targets
- Support hardware deployment and basic troubleshooting on partner premises
- Communicate regularly with internal teams (product, strategy) and partner contacts
- Help identify and implement process improvements based on operational feedback
Ideally you'd have:
- Strong professional communication skills in both Spanish and English.
- Bachelor’s degree in Business Administration, Economics, Logistics, Industrial Engineering, or related fields (open to both technical and non-technical degrees).
- Industry experience (+2) in physical/on-site operations, logistics, business development, account management or analytics.
- Experience in the field: warehouses, factories, logistics centers.
- Analytical, strategic, and process improvement capability.
Nice to haves:
- SQL Proficiency
- Experience working with CRM systems
This role involves both on-site presence for coordinating operations as well as visiting partner sites on a daily basis.
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, Ernst & Young, 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.
We comply with the United States Department of Labor's Pay Transparency provision.
PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Skills Required
- Strong professional communication skills in both Spanish and English
- Bachelor's degree in Business Administration, Economics, Logistics, Industrial Engineering, or related field
- 2+ years industry experience in physical/on-site operations, logistics, business development, account management, or analytics
- Experience working in warehouses, factories, or logistics centers
- Analytical, strategic, and process improvement capability
- Support hardware deployment and perform basic troubleshooting on partner premises
- SQL proficiency
- Experience working with CRM systems
- Ability to be on-site regularly and visit partner sites on a daily basis
Scale AI Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Scale AI and has not been reviewed or approved by Scale AI.
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Healthcare Strength — Healthcare coverage is described as comprehensive across medical, dental, and vision, with flexibility to choose plans that fit individual or family needs. A monthly wellness stipend further supports physical and mental wellbeing expenses.
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Equity Value & Accessibility — Equity-based compensation is included in eligible packages, positioning ownership as a meaningful component of total rewards for many full-time roles. An employee stock purchase plan also provides an additional pathway to participate in potential upside.
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Leave & Time Off Breadth — Paid time off is positioned as generous with a flexible policy intended to support recharging and burnout prevention. Paid holidays and paid sick days are also part of the time-off offering.
Scale AI Insights
What We Do
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.
