MLEngineer

Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. Docker's long-term vision is to become the runtime for trusted autonomy. As agents become more capable and autonomous, governance, policy, identity, and audit become foundational. The Intelligence team builds intelligence-driven product capabilities that make software and agent execution on Docker safer, more effective, more trustworthy, and more efficient. Because Docker sits at the intersection of models, tools, software, identities, credentials, networks, and execution, we have visibility into behavior and context few other platforms can see, and we think that visibility is the foundation for a new layer of value across the platform. ABOUT THE ROLE We're hiring a ML Engineer as one of the founding engineers on Intelligence Org. You'll work directly with the team's first engineers and manager to figure out what to build, how to build it, and how it fits into the broader Docker platform. This is a hands-on builder role with staff-level scope: you'll shape technical direction, ship the first versions of intelligence capabilities into customer hands, and grow the foundations (data, evaluation, infrastructure) the team will rely on as it scales. RESPONSIBILITIES - Design, train, evaluate, and ship ML systems that power governance and security capabilities, starting with problems