Senior Machine Learning Engineer - Model Evaluations, Public Sector
Job in
San Francisco, San Francisco County, California, 94199, USA
Listed on 2026-04-17
Listing for:
Scale AI
Full Time
position Listed on 2026-04-17
Job specializations:
-
IT/Tech
AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist
Job Description & How to Apply Below
The Public Sector ML team at Scale deploys advanced AI systems—including LLMs, agentic models, and multimodal pipelines—into mission-critical government environments. We build evaluation frameworks that ensure these models operate reliably, safely, and effectively under real-world constraints. As an ML Engineer, you will design, implement, and scale automated evaluation pipelines that help customers trust and operationalize advanced AI systems across defense, intelligence, and federal missions.
You will:
- Develop and maintain automated evaluation pipelines for ML models across functional, performance, robustness, and safety metrics, including LLM-judge–based evaluations.
- Design test datasets and benchmarks to measure generalization, bias, explainability, and failure modes.
- Build evaluation frameworks for LLM agents, including infrastructure for scenario-based and environment-based testing.
- Conduct comparative analyses of model architectures, training procedures, and evaluation outcomes.
- Implement tools for continuous monitoring, regression testing, and quality assurance for ML systems.
- Design and execute stress tests and red-teaming workflows to uncover vulnerabilities and edge cases.
- Collaborate with operations teams and subject matter experts to produce high-quality evaluation datasets.
Ideally you’d have:
- Experience in computer vision, deep learning, reinforcement learning, or NLP in production settings.
- Strong programming skills in Python; experience with Tensor Flow or PyTorch.
- Background in algorithms, data structures, and object-oriented programming.
- Experience with LLM pipelines, simulation environments, or automated evaluation systems.
- Ability to convert research insights into measurable evaluation criteria.
- Graduate degree in CS, ML, or AI.
- Cloud experience (AWS, GCP) and model deployment experience.
- Experience with LLM evaluation, CV robustness, or RL validation.
- Knowledge of interpretability, adversarial robustness, or AI safety frameworks.
- Familiarity with ML evaluation frameworks and agentic model design.
- Experience in regulated, classified, or mission-critical ML domains.
Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to:
Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.
Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:
$240,450—$300,300 USD
Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of Washington DC, Texas, Colorado, Hawaii is:
$216,300—$269,850 USD
PLEASE NOTE:
Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
About Us:
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work…
Position Requirements
10+ Years
work experience
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