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Senior Machine Learning Engineer, Public Sector

Scale AI· Public Sector Engineering
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Hybrid (Denver, CO; Honolulu, HI; Washington, DC)$163.2k - $204kfull-timePosted 1mo ago

About the role

Senior MLE responsible for designing and delivering agentic AI, generative AI, computer vision, and reinforcement learning solutions for government systems, including Donovan and Thunderforge, with end-to-end ownership from architecture to production and evaluation in secure environments.

Responsibilities

  • Own the design and delivery of agent capabilities end to end - architecture, implementation, and the evaluation that proves they work
  • Define net-new patterns in problem spaces with no established approach, propose them to the wider team, and lead the work to build them
  • Take state of the art models developed internally and from the community and put them into production to solve problems for our customers and taskers
  • Improve and maintain production models and agents through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics
  • Build agent-level evaluation benchmarks, LLM judges, and verifiers - and use it to hillclimb performance rather than just report on it
  • Partner with product and research teams to scope and shape high-impact initiatives, including for upcoming product lines
  • Build scalable machine learning infrastructure to automate and optimize our ML services
  • Work directly with government users and subject-matter experts, and translate what you learn into technical direction
  • Act as a force multiplier and a primary reviewer for your team, mentoring at least one engineer, and your manager's go-to on feasibility questions
  • Communicate technical tradeoffs clearly to non-technical stakeholders
  • Treat security and compliance as design constraints to engineer around rather than blockers to route past
  • Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations
  • Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment
  • Comfortable with light travel (approximately 10%) for customer interaction and team needs

Qualifications

  • 5+ years of experience building and deploying applied ML systems in production environments
  • Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment
  • A track record of owning architectural decisions and defending the tradeoffs behind them - not just implementing a design handed to you
  • Experience shipping agentic systems with real production traffic and evaluation rigor, rather than prototypes or demos
  • Solid background in algorithms, data structures, and object-oriented programming
  • Strong programming skills in Python, experience in PyTorch or Tensorflow
  • Experience mentoring or reviewing the work of other engineers

Skills

Required:PythonPyTorch or TensorFlow

Benefits

  • comprehensive health, dental and vision coverage
  • retirement benefits
  • learning and development stipend
  • generous PTO
  • commuter stipend (may be eligible)
Last updated Oct 21, 2026. Interested? Apply on the company site.
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About Scale AI

Data-centric infrastructure to accelerate the development of AI

Scale accelerates the development of AI within organizations of any size to deliver critical business insights and operational efficiency. Its data-centric infrastructure platform leverages RLHF (Reinforced Learning with Human Feedback) to help organizations build the strongest AI models that supercharge their business, with customers across industries including Meta, Microsoft, U.S. Army, DoD’s Defense Innovation Unit, Open AI, General Motors, Toyota Research Institute, Brex, Instacart and Flexport.

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