# Staff Machine Learning Engineer, Public Sector

**Company:** [Scale AI](https://hotfix.jobs/companies/scale-ai)
**Location:** Denver, CO, Honolulu, HI, Washington, DC
**Role:** ML Engineering
**Salary:** $274k – $343k/yr
**Experience:** 8+ years
**Skills:** Python, PyTorch, Agentic AI, Machine Learning, Ml Systems, Model Serving, Retrieval Systems, Embeddings, Representation Learning, Geospatial Data, Geoint, Lora, Peft, RLHF, Evaluation Infrastructure
**Posted:** 2026-09-10

> Leads architecture, deployment, and evaluation of reliable agentic ML systems for classified and regulated government environments, including geospatial reasoning, retrieval, memory, and shared infrastructure. Requires 8+ years of production ML experience, Staff-level technical leadership, Python, PyTorch, and an active TS clearance.

## Job Description

## Responsibilities
- Lead the architecture and implementation of agentic AI systems focused on long-horizon reasoning, orchestration, and system reliability.
- Build and scale agents for geospatial reasoning over maps and spatial data.
- Design and improve retrieval systems across large collections of static and semi-structured documents.
- Fine-tune and evaluate embedding models for mission-critical datasets.
- Design memory systems for persistent state, long contexts, and learning from prior interactions.
- Own and evolve shared agentic infrastructure and core libraries.
- Define evaluation strategies, robustness tests, failure-mode analyses, and production regression tests for agentic systems.
- Partner with engineering managers, product leaders, and researchers to scope initiatives and unblock execution.
- Mentor engineers and raise standards for system design, ML rigor, and production readiness.
- Travel approximately 10% for customer interaction and team needs.

## Requirements
- Active TS security clearance.
- 8+ years building and deploying applied machine learning systems in production.
- Experience with agentic systems, autonomous workflows, or multi-step reasoning and acting systems.
- Strong ML systems engineering background, including model serving, pipelines, monitoring, and evaluation.
- Hands-on experience with retrieval systems, embeddings, or representation learning.
- Proficiency in Python and modern machine learning frameworks such as PyTorch.
- Ability to design systems end to end and operate at Staff-level scope.
- Experience setting technical direction, owning ambiguous problems, and taking initiatives from 0 to 1 through production.
- Ability to balance performance, cost, reliability, and development velocity.

## Nice-to-haves
- Experience deploying ML systems in air-gapped, classified, disconnected, on-premises, or customer data-center environments.
- Experience with the Department of Defense, intelligence community, or federal mission users.
- Experience with geospatial data or GEOINT, including maps, imagery, or spatial reference systems.
- Experience with model adaptation, embedding-model fine-tuning, instruction tuning, LoRA/PEFT, or RLHF.
- Experience building evaluation infrastructure for non-deterministic systems, including LLM-as-judge, agent regression suites, or production drift detection.
- Experience turning forward-deployed prototypes into supported and documented capabilities.

## Compensation
- Base salary for Washington, DC: **$274,400–$343,000 USD**.
- Eligible roles may include equity and benefits such as health, dental and vision coverage, retirement benefits, a learning and development stipend, PTO, and potentially a commuter stipend.

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