Staff ML Engineer - Agentic AI for Geospatial Reasoning

Scale AI; Washington (District of Columbia); On-site; USD 274,000 - 343,000; Full time

Benefits offered by this job

Health, dental and vision coverage

Retirement benefits

Learning stipend

Generous PTO

Commuter stipend

Job summary

Scale AI is seeking a Staff Machine Learning Engineer for the Public Sector team to lead design and deployment of agentic AI systems in government environments. You’ll partner with defense and intelligence programs to advance geospatial reasoning, planning, and decision support at national scale.

The role emphasizes owning core architectures, mentoring teams, and delivering robust, production-grade ML systems with awareness of security and regulatory requirements.

Qualifications

• 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 (e.g. PyTorch).
• 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.

Responsibilities

• Lead the architecture and implementation of agentic AI systems with long-horizon reasoning and system-level reliability.
• Build and scale agents for geospatial reasoning and spatial data interpretation.
• Design and improve retrieval systems over large document collections for high-signal context.
• Fine-tune embedding models to improve recall and precision on mission-critical data.
• Design memory systems for long contexts and state persistence across interactions.
• Own and evolve shared agentic infrastructure and core libraries for reuse.
• Define evaluation strategies including robustness testing and regression in production.
• Collaborate with managers, product leaders, and researchers to scope high-impact initiatives.

Skills

Agentic ML systems

Long-horizon reasoning

Python

PyTorch

System design

Tools

Retrieval systems

Embeddings

Model serving

Evaluation pipelines

Job description

Scale AI is seeking a Staff Machine Learning Engineer for the Public Sector team to lead design and deployment of agentic AI systems in government environments. You’ll partner with defense and intelligence programs to advance geospatial reasoning, planning, and decision support at national scale.

The role emphasizes owning core architectures, mentoring teams, and delivering robust, production-grade ML systems with awareness of security and regulatory requirements.