Machine Learning Engineering Manager, Public Sector
At Scale, our Public Sector Machine Learning team develops and deploys cutting-edge AI systems into mission-critical government environments. From advanced computer vision pipelines to agentic LLM frameworks, our work directly supports national security and defense partners. We are looking for a Machine Learning Engineering Manager to lead this team of world-class ML engineers and help shape the future of AI in the public sector.
As a Machine Learning Engineering Manager, you will combine strong technical expertise with people leadership. You'll guide the team in delivering production-grade ML systems across modalities while ensuring alignment with product, research, and government partner needs. Leveraging large language models, computer vision, reinforcement learning, and agentic AI, you will lead research projects and harden them into scalable production systems. This role requires someone who can balance hands-on technical oversight, mentorship, and execution strategy in a fast-paced, mission-driven environment.
You will:
- 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.
- Cultivate a strong engineering culture that values collaboration, innovation, accountability, and impact.
- Support career development, performance reviews, and hiring to expand the team.
Ideally you'd have:
- 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.
- 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.).
- 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.
Nice to haves:
- Graduate degree in Computer Science, Machine Learning, or related field.
- Experience in public sector / defense AI programs.
- Familiarity with evaluation frameworks for LLMs and multi-agent systems.
- Cloud platform (AWS/GCP/Azure) experience, especially in secure deployments.