Scale is the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world's most important decisions.
We are looking for an AI Product Manager to support Multimodal & Coding AI data verticals, including audio, image, video, and world models. This role is designed for someone early in their product career who is excited about AI and wants to develop into a full AI Product Manager over time.
In this role, you will work closely with Senior AI Product Managers to drive execution across product, operations, and customer programs. You will help coordinate cross-functional initiatives, manage project timelines, support customer engagements, and contribute to product discovery and data development efforts. This position offers a clear growth path into AI Product Management, with increasing ownership of products, customer relationships, and business outcomes.
You Will- Partner with Senior AI Product Managers to drive execution of strategic initiatives across Coding, Agentic, and RL data products.
- Coordinate cross-functional projects across operations, engineering, research, and go-to-market teams to ensure timely delivery of customer commitments.
- Track program milestones, risks, dependencies, and deliverables while driving accountability across stakeholders.
- Support customer engagements by preparing materials, documenting requirements, coordinating follow-ups, and helping manage project execution.
- Assist in defining data specifications, reviewing data quality, and identifying opportunities to improve product performance and operational efficiency.
- Conduct market, customer, and competitive research to inform product strategy and roadmap decisions.
- Contribute to the development of new AI data products, tooling, and evaluation workflows.
- Develop a strong understanding of frontier AI models, agent systems, and data pipelines, with increasing ownership over product decisions over time.
- 3 years of experience in product management, project management, product operations, consulting, technical account management, customer success, or a related role.
- Strong organizational skills with the ability to manage multiple projects and stakeholders simultaneously.
- Excellent written and verbal communication skills.
- Demonstrated ability to work effectively in cross-functional environments and drive projects to completion.
- Technical curiosity and a desire to learn about AI systems, machine learning, coding, or data products.
- Experience working with technical teams or customers is a plus.
- A bias for action, strong ownership mentality, and willingness to operate in fast-moving environments.
- Bachelor's degree in Computer Science, Engineering, Business, or a related field (or equivalent practical experience).
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 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, 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
- 6+ years of experience in product management or a customer-facing role
- Software engineering background (degree in computer science or equivalent experience)
- Understanding of reinforcement learning, simulation environments, or data pipelines for model training and evaluation
- Entrepreneurial mindset and ability to build new products from ambiguity
- Strong customer intuition and ability to translate technical requirements into product decisions
- Bias for action and comfort wearing multiple hats in fast-moving environments
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 — Company materials and third‑party pages describe comprehensive medical, dental, and vision coverage along with mental‑health services and an EAP. Health insurance is portrayed as strong, with options like HSA/FSA and indications of high premium coverage.
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Leave & Time Off Breadth — Descriptions highlight generous PTO, paid holidays and sick time, bereavement, volunteer time, and role‑dependent flexibility or remote options. This breadth is positioned as part of a supportive time‑off approach, with specifics varying by location.
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Equity Value & Accessibility — Full‑time offers commonly include equity and an ESPP, which can meaningfully lift total compensation, especially in engineering and senior roles. Job postings and compensation snapshots consistently reference base‑plus‑equity packages aligned with competitive AI market pay.
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.
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