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Scale's Public Sector Machine Learning team needs to develop and deploy cutting-edge AI systems into mission-critical government environments to support national security and defense partners. The company is looking for a Machine Learning Engineering Manager to lead this team and shape the future of AI in the public sector.

Requirements

• Strong technical background in one or more of: computer vision, generative AI/LLMs, reinforcement learning, or agentic systems.
• Up-to-date understanding of cutting edge ML research and production systems in your domain(s) of expertise.
• Hands-on experience with deep learning frameworks (PyTorch, TensorFlow) and large-scale ML infrastructure.
• Background in deploying AI systems in high-reliability or mission-critical contexts (public sector, defense, healthcare, finance, etc.).
• Familiarity with evaluation frameworks for LLMs and multi-agent systems.
• Cloud platform (AWS/GCP/Azure) experience, especially in secure deployments.

Responsibilities

• Lead and grow a team of ML engineers delivering production-ready AI systems for public sector customers.
• Provide technical direction and mentorship on projects spanning agentic LLM frameworks, reinforcement learning, generative AI, and computer vision.
• Collaborate with research, product, and infrastructure teams to align technical roadmaps with organizational and customer priorities.
• Drive operational excellence: establish best practices for model development, deployment, evaluation, and monitoring in secure, high-stakes environments.
• Partner with public sector stakeholders to translate mission needs into scalable ML solutions.
• Work closely with public sector customers to scope and deliver AI applications.
• Ensure effective prioritization and resourcing across multiple programs and customer engagements.

Other

• US citizenship and US Government Security Clearance is a requirement (TS/SCI preferred)
• Proven experience managing and mentoring ML or AI engineering teams, ideally in applied research or production ML environments.
• Ability to communicate technical concepts effectively to both technical and non-technical stakeholders, including government partners.
• Strong program management skills: ability to set strategy, manage multiple priorities, and deliver on commitments.
• Cultivate a strong engineering culture that values collaboration, innovation, accountability, and impact.
• Support career development, performance reviews, and hiring to expand the team.