Scale AI · 4 hours ago
Staff Machine Learning Engineer, Public Sector
San Francisco Bay Area
Full-time
Onsite
Lead/Staff
$260K/yr - $327K/yr
8+ years expScale AI is a company focused on developing reliable AI systems for important decisions. They are seeking a Staff Machine Learning Engineer to lead the design and deployment of agentic AI systems in mission-critical government environments, working closely with U.S. defense and intelligence agencies.
AI InfrastructureArtificial Intelligence (AI)Data Collection and LabelingGenerative AIImage RecognitionMachine Learning
No H1B
Security Clearance RequiredU.S. Citizen Only
Responsibilities
Lead the architecture and implementation of agentic AI systems, with a focus on long-horizon reasoning, orchestration, and system-level reliability
Build and scale agents that perform complex geospatial reasoning, including interpreting, generating, and reasoning over maps and spatial data
Design and improve retrieval systems across large collections of static and semi-structured documents, enabling agents to surface high-signal context efficiently
Fine-tune and evaluate embedding models to improve recall and precision for mission-critical datasets
Design memory systems that allow agents to persist state, operate over long contexts, and learn from prior interactions
Own and evolve shared agentic infrastructure and core libraries, enabling reuse across teams, products, and Public Sector contracts
Define evaluation strategies for agentic systems, including robustness testing, failure-mode analysis, and regression testing in production environments
Partner closely with engineering managers, product leaders, and researchers to scope high-impact initiatives and unblock execution across teams
Serve as a technical mentor and multiplier—raising the bar for system design, ML rigor, and production readiness across the organization
Qualification
Required
Lead the architecture and implementation of agentic AI systems, with a focus on long-horizon reasoning, orchestration, and system-level reliability
Build and scale agents that perform complex geospatial reasoning, including interpreting, generating, and reasoning over maps and spatial data
Design and improve retrieval systems across large collections of static and semi-structured documents, enabling agents to surface high-signal context efficiently
Fine-tune and evaluate embedding models to improve recall and precision for mission-critical datasets
Design memory systems that allow agents to persist state, operate over long contexts, and learn from prior interactions
Own and evolve shared agentic infrastructure and core libraries, enabling reuse across teams, products, and Public Sector contracts
Define evaluation strategies for agentic systems, including robustness testing, failure-mode analysis, and regression testing in production environments
Partner closely with engineering managers, product leaders, and researchers to scope high-impact initiatives and unblock execution across teams
Serve as a technical mentor and multiplier—raising the bar for system design, ML rigor, and production readiness across the organization
This role will require an active security clearance or the ability to obtain a security clearance
8+ years of experience building and deploying applied ML systems in production environments
Deep experience with agentic systems, autonomous workflows, or ML systems that reason and act over multiple steps
Strong background in ML systems engineering, including model serving, pipelines, monitoring, and evaluation
Hands-on experience with retrieval systems, embeddings, or representation learning
Proficiency in Python and modern ML frameworks (ex: PyTorch), with the ability to design systems end to end
Demonstrated ability to operate at Staff-level scope: setting technical direction, owning ambiguous problems, and driving 0→1 initiatives to production
Experience making thoughtful tradeoffs across performance, cost, reliability, and development velocity
Preferred
High ownership over 0→1 systems that move directly into production
Real-world constraints that force thoughtful engineering tradeoffs, not just model tuning
Opportunity to shape foundational agentic infrastructure used across multiple teams and missions
Work that blends research depth with applied impact, in environments where correctness, robustness, and trust matter
Benefits
Comprehensive health, dental and vision coverage
Retirement benefits
A learning and development stipend
Generous PTO
Commuter stipend
Company
Scale AI
Scale’s mission is to develop reliable AI systems for the world’s most important decisions.
501-1000 employees
Funding
Current Stage
Late StageTotal Funding
$15.9BKey Investors
MetaAccelTiger Global Management
2025-06-10Corporate Round· $14.3B
2025-06-04Series Unknown
2024-05-21Series F· $1B
Leadership Team
Jason Droege
Interim Chief Executive Officer
Clemens Viernickel
Head of Product
Recent News
2026-01-16
CB Insights
2026-01-09
Crunchbase News
2026-01-07
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