Scale AI

AI Product Manager to own the Agent & Reinforcement Learning Environments data vertical, focusing on Computer Using Agent (CUA) data. Responsibilities include owning the product roadmap, data generation pipelines, quality, and researcher-facing tools for training and evaluating intelligent agents. Requires a blend of entrepreneurial, go-to-market, and technical skills, with experience in product management and understanding of RL, simulation environments, and data pipelines for model training/evaluation.

Product Manager for AI Applications within Scale AI's Global Public Sector team, focusing on developing bespoke AI solutions for governments and government-backed entities. This role involves leading cross-functional teams to build custom AI applications and LLMs, leveraging the Scale GenAI Platform, and ensuring customer success through client workshops, use case scoping, and continuous feedback.

Product Manager for GenAI Test & Evaluation (T&E) in the Public Sector team at Scale AI. This role focuses on defining the vision and roadmap for evaluation capabilities, owning the T&E tech stack to measure and improve agentic applications. Requires strong engineering depth, experience with evaluation systems, problem distillation, ambiguity management, cross-functional leadership, and operational execution. Experience with GenAI implementation, public sector work, and security clearance are preferred.

Staff Technical Product Manager for Scale AI's Global Public Sector team, focusing on defense and national security customers. The role involves owning product roadmaps, writing specs, prototyping, and shipping AI-powered products and tooling for defense workflows, requiring a strong engineering or ML background and a hands-on builder mentality.

Product Manager for GenAI at Scale AI, focusing on building data infrastructure and tooling for AI model training and evaluation. The role involves shaping products for both customers (demand side) and contributors (supply side), requiring end-to-end product ownership from strategy to execution. The position is cross-functional, working with engineering, design, and data science teams in a fast-paced, growth-stage environment.

Product Manager for Scale AI's Public Sector Data Engine, focusing on building ML Ops infrastructure for computer vision and generative AI models used in national security systems. The role involves architecting the AI engine, managing roadmaps, technical scoping, and operationalizing collaboration between engineering, operations, and government stakeholders.

Product Manager role focused on building and deploying enterprise-grade Generative AI solutions for customers, leveraging Scale's GenAI Platform. The role involves owning AI projects end-to-end, defining product strategy, and leading cross-functional teams to deliver AI applications that drive business value.

Scale AI is seeking a GenAI Strategic Projects Lead for their Public Sector team in Washington, DC. This role will own high-impact projects focused on generative AI data labeling pipelines, operational processes for data workforce management, and improving training/evaluation dataset quality for public sector customers, particularly in national security. The role involves developing infrastructure, managing data production pipelines, partnering with SMEs and customers, and influencing cross-organizational strategy to enable mission-critical AI applications.

This role focuses on delivering agentic AI solutions for homeland defense clients, managing customer relationships, and partnering with engineering to build and deploy AI systems tailored to government use cases in computer vision and generative AI.

This role is a Technical Program Manager for Scale AI's Public Sector division, focusing on customer success and driving the delivery of AI/ML solutions. The TPM will manage technical projects, leverage data and analytics to solve customer problems, and partner with engineering teams to deliver AI systems tailored to government use cases in computer vision and generative AI. The role requires a technical background, understanding of ML operations, and experience in stakeholder management within a regulated environment.