Staff Machine Learning Engineer, Public Sector
$274k - $343k • Denver, CO; Washington, DC
Posted 5d ago
Job Location
Denver, CO; Washington, DC
Tech Stack
Remote Work Policy
On-site
Categories
Machine Learning Engineer
About the job
Scale is seeking a Staff Machine Learning Engineer for its Public Sector team to lead the design and deployment of agentic AI systems in critical government environments. This role involves working at the intersection of agentic ML, systems engineering, and applied research to build foundational infrastructure for AI systems that reason, plan, and act reliably at a national scale. You will partner directly with U.S. defense and intelligence agencies, contributing to flagship programs that advance agentic AI for geospatial reasoning, planning, and decision support. As a Staff ML Engineer, you will set technical direction, own core architectures, and translate ambitious ideas into production systems trusted by government operators.
Responsibilities
- Lead the architecture and implementation of agentic AI systems, focusing on long-horizon reasoning, orchestration, and system-level reliability.
- Build and scale agents for complex geospatial reasoning, including interpreting, generating, and reasoning over maps and spatial data.
- Design and improve retrieval systems for large document collections to enable efficient context surfacing.
- Fine-tune and evaluate embedding models to enhance recall and precision for mission-critical datasets.
- Design memory systems for agents to persist state, operate over long contexts, and learn from interactions.
- Own and evolve shared agentic infrastructure and core libraries for cross-team and cross-product reuse.
- Define evaluation strategies for agentic systems, including robustness testing, failure-mode analysis, and production regression testing.
- Partner with engineering managers, product leaders, and researchers to scope initiatives and unblock execution.
- Serve as a technical mentor, raising the bar for system design, ML rigor, and production readiness.
- Travel approximately 10% for customer interaction and team needs.
Requirements
- 8+ years of experience building and deploying applied ML systems in production.
- Deep experience with agentic systems, autonomous workflows, or multi-step reasoning/acting ML systems.
- 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 (e.g., PyTorch), with end-to-end system design capabilities.
- Demonstrated ability to operate at a Staff-level scope: setting technical direction, owning ambiguous problems, and driving 0→1 initiatives.
- Experience making tradeoffs across performance, cost, reliability, and development velocity.
- An active TS security clearance is required.
Benefits
- Base salary
- Equity
- Comprehensive health, dental, and vision coverage
- Retirement benefits
- Learning and development stipend
- Generous PTO
- Commuter stipend (potential eligibility)