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Machine Learning Engineering Manager, Public Sector
Machine Learning Engineering Manager, Public SectorScale AI, Inc. • Washington, DC, United States
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Machine Learning Engineering Manager, Public Sector

Machine Learning Engineering Manager, Public Sector

Scale AI, Inc. • Washington, DC, United States
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Overview

At Scale, our Public Sector Machine Learning team develops and deploys AI systems into mission-critical government environments. We work on computer vision pipelines and agentic LLM frameworks to support national security and defense partners. We are seeking a Machine Learning Engineering Manager to lead this team of ML engineers and help shape the future of AI in the public sector.

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.
  • Cultivate a strong engineering culture that values collaboration, innovation, accountability, and impact.
  • Support career development, performance reviews, and hiring to expand the team.

Qualifications

  • 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 experience (AWS / GCP / Azure), especially in secure deployments.
  • About compensation and location

    Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The base salary range for this full-time position in the locations of San Francisco, New York, Seattle is $229,000 — $286,000 USD . For Washington DC, the base salary range is $206,000 — $257,000 USD .

    Additional details : eligibility for equity grants and other benefits vary by location and role. Your recruiter can share the specific salary range for your location during the hiring process.

    PLEASE NOTE : Our policy requires a 90-day waiting period before reconsidering candidates for the same role.

    About Us and Equal Opportunity

    At Scale, our mission is to develop reliable AI systems for the world's most important decisions. We work with industry leaders and government agencies to accelerate AI applications. We are an inclusive and equal opportunity workplace and comply with applicable laws. We provide accommodations on request during the application process.

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    Engineering Manager • Washington, DC, United States

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