Senior Machine Learning Engineer, Public Sector

Washington, DCfull timeOn Site

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senior

$235k–$294k

H1B: yes

Scale AI The Senior Machine Learning Engineer at Scale AI designs and delivers agent capabilities using generative AI and reinforcement learning for mission-critical government systems. This role involves building scalable ML infrastructure and working directly with government users and subject-matter experts.

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

Qualification

Graduate degree in Computer ScienceExperience with computer visionExperience deploying ML in classifiedGeospatial or GEOINT experienceInference optimization experienceFine-tuning experience

Preferred

Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization
Experience working with cloud platforms (eg. AWS or GCP) and deploying machine learning models in cloud environments
Experience with computer vision, generative AI models, large language models, or agentic systems
Familiarity with ML evaluation frameworks and agentic model design
Experience deploying ML in classified, air-gapped, or IL5+ environments
Geospatial or GEOINT experience
Inference optimization experience
Fine-tuning experience: SFT, RL, or embedding models