Staff ML Engineer: Agentic AI for Geospatial Defense

Scale AI, Inc.; 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 and development stipend

Generous PTO

Commuter stipend

Job summary

Scale AI, Inc. seeks a Staff Machine Learning Engineer for the Public Sector to design and deploy agentic AI systems in government environments in Washington, DC.

You will lead architectures, build agents for geospatial tasks, and surface high‑signal context in large document collections. You will also tune embeddings, design memory systems, and mentor teams while partnering with managers and researchers to drive production‑ready capabilities.

Qualifications

• 8+ years of experience building and deploying applied ML systems.
• Deep experience with agentic systems, autonomous workflows, or multi-step reasoning.
• Strong background in ML systems engineering (model serving, pipelines, monitoring, 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.
• Capability to operate at Staff‑level scope: set direction, own ambiguous problems, drive initiatives to production.
• Experience making trade-offs across performance, cost, reliability and development velocity.

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 documents to surface 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 over long contexts and learn from interactions.
• Own and evolve shared agentic infrastructure and core libraries for reuse across teams and contracts.
• Define evaluation strategies for robustness and regression testing in production.
• 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 and production readiness.
• Comfortable with light travel (~10%) for customer interaction.

Skills

Agentic ML

ML systems eng

Python

PyTorch

Staff-level leadership

Retrieval systems

Geospatial reasoning

System design

Trade-offs

Tools

PyTorch

Job description

Scale AI, Inc. seeks a Staff Machine Learning Engineer for the Public Sector to design and deploy agentic AI systems in government environments in Washington, DC.

You will lead architectures, build agents for geospatial tasks, and surface high‑signal context in large document collections. You will also tune embeddings, design memory systems, and mentor teams while partnering with managers and researchers to drive production‑ready capabilities.