---
title: 'Senior Machine Learning Engineer, Public Sector at Scale AI'
canonical: 'https://feeny.ai/job/senior-machine-learning-engineer-public-sector-scale-ai-denver-bp9tff13vfs8'
type: 'job'
last_seen: '2026-09-16'
---

# Senior Machine Learning Engineer, Public Sector at Scale AI

- **Company:** Scale AI
- **Location:** Denver, CO / Honolulu, HI / Washington, DC
- **Compensation:** $235k–$294k
- **Posted:** 2026-09-10
- **Last confirmed live:** 2026-09-16
- **Apply:** https://job-boards.greenhouse.io/scaleai/jobs/4732798005

## Job description

The goal of a Senior Machine Learning Engineer at Scale is to own how we apply generative AI, agentic AI, computer vision, and reinforcement learning to mission-critical problems in production. Our senior machine learning engineers are handed problems that don't yet have an established approach, they propose the architecture, build it with support from other engineers, and are accountable for whether it holds up in the environments our customers depend on.

Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like [Donovan](https://scale.com/blog/meet-the-legend-behind-the-name-scale-donovan) and [Thunderforge](https://scale.com/blog/thunderforge-ai-for-american-defense). Our work spans multiple modalities, with our primary focus on agentic systems built on large language models. We are developing agents that solve complex operational and planning challenges for government partners: agent frameworks that integrate custom retrieval pipelines and production APIs, memory and context-management systems that hold state across long-running tasks, geospatial reasoning over maps and spatial data, and the evaluation tooling that benchmarks and refines agent behavior. We also apply reinforcement learning in targeted places where it earns its keep, and our computer vision work advances evaluation, labeling efficiency, and multimodal model training in support of defense applications.

As a Senior MLE, you'll have design authority over a capability area - the final say on the patterns used within your team, and the responsibility to make those patterns work under real constraints: classified environments, limited compute, and correctness requirements that don't bend.

You will:

- Own the design and delivery of agent capabilities end to end - architecture, implementation, and the evaluation that proves they work
- Define net-new patterns in problem spaces with no established approach, propose them to the wider team, and lead the work to build them
- Take state of the art models developed internally and from the community and put them into production to solve problems for our customers and taskers
- Improve and maintain production models and agents through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics
- Build agent-level evaluation benchmarks, LLM judges, and verifiers - and use it to hillclimb performance rather than just report on it
- Partner with product and research teams to scope and shape high-impact initiatives, including for upcoming product lines
- Build scalable machine learning infrastructure to automate and optimize our ML services
- Work directly with government users and subject-matter experts, and translate what you learn into technical direction
- Act as a force multiplier and a primary reviewer for your team, mentoring at least one engineer, and your manager's go-to on feasibility questions
- Communicate technical tradeoffs clearly to non-technical stakeholders
- Treat security and compliance as design constraints to engineer around rather than blockers to route past
- Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations
- Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment
- Comfortable with light travel (approximately 10%) for customer interaction and team needs

This role will require an active TS security clearance

Ideally You'd Have:

- 5+ years of experience building and deploying applied ML systems in production environments
- Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment
- A track record of owning architectural decisions and defending the tradeoffs behind them - not just implementing a design handed to you
- Experience shipping agentic systems with real production traffic and evaluation rigor, rather than prototypes or demos
- Solid background in algorithms, data structures, and object-oriented programming
- Strong programming skills in Python, experience in PyTorch or Tensorflow
- Experience mentoring or reviewing the work of other engineers

Nice to Haves:

- Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization
- Experience working with cloud platforms (eg. AWS or GCP) and deploying machine learning models in cloud environments
- Experience with computer vision, generative AI models, large language models, or agentic systems
- Familiarity with ML evaluation frameworks and agentic model design
- Experience deploying ML in classified, air-gapped, or IL5+ environments
- Geospatial or GEOINT experience
- Inference optimization experience
- Fine-tuning experience: SFT, RL, or embedding models

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

The base salary range for this full-time position in the location of Washington DC is: $235,200—$294,000 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's [Know Your Rights poster](https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) for additional information.

We comply with the United States Department of Labor's Pay Transparency provision.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our [privacy policy](https://scale.com/legal/privacy) for additional information.

## About Scale AI

## Company Overview
- **One-liner**: Scale AI provides high-quality data, RLHF, model evaluations, and full-stack AI infrastructure to help enterprises and governments build, deploy, and oversee reliable AI systems.
- **Entity Type**: Private (49% non‑voting stake owned by Meta Platforms as of June 2025; total funding $1.6B across eight rounds)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2016
- **Founders**: Alexandr Wang, Lucy Guo (Wang left in June 2025; current CEO is Jason Droege)

## Core Business
- **Primary industry**: AI infrastructure, data annotation, large language model (LLM) evaluation, enterprise AI deployment
- **Target customers**: B2B – Enterprise and government organizations; also serves leading AI labs (e.g., OpenAI, Google DeepMind, Meta, Microsoft, General Motors)
- **Mission**: “Develop reliable AI systems for the world's most important decisions.”

## Products & Services
- **Data at Scale**: High-quality training data, annotations, and RLHF for advanced AI models (SaaS + human-in-the-loop service)
- **Evaluations**: Rigorous model evaluations, benchmarking, and red‑teaming to measure and improve AI performance (service)
- **Applied AI**: Full‑stack AI systems that help enterprises and governments build, deploy, and oversee reliable AI (SaaS + consulting)
- **Safety, Evaluation and Alignment Lab**: Research arm focused on LLM alignment and safety (internal R&D; also co‑created the “Humanity's Last Exam” benchmark)
- **Subsidiaries**: Remotasks (computer vision and autonomous vehicle data labeling), Outlier (LLM data annotation)

## Market Standing
- **Valuation**: $29B (as of 2025 – cited on scale.com)
- **Key Metric**: Total Funding – $1.6B (including the $14B Meta investment that acquired a 49% non‑voting stake in June 2025)
- **Notable Investors/Partners**: Meta Platforms (49% owner), with commercial customers including Google, Microsoft, Meta, General Motors, OpenAI, and Time. Also works with U.S. and Qatari governments.
- **Growth Signals**:
  - Headcount: Scale.com cites “1,000+” employees; LinkedIn reports 3,751 employees (+32.1% YoY).
  - 90% of the world’s leading generative AI model builders are powered by Scale.
  - 15 billion human decisions used to train AI models; $1 billion paid to contributors globally.
  - Active job postings: 284+ (as of July 2025), with strong hiring in enterprise engineering, AI agents, and solutions roles.

## Competitive Advantages
- **Data moat**: Scale’s proprietary Data Engine and access to millions of human‑annotated decisions create high‑quality training data that competitors cannot easily replicate.
- **Trust & adoption**: Used by 90% of leading GenAI builders; runs private benchmarks for the most ambitious AI companies.
- **Government credibility**: Direct contracts with the U.S. Department of Defense and international governments (e.g., Qatar) – a high‑barrier entry point.
- **Full‑stack offering**: From raw data annotation to LLM evaluation and end‑to‑end applied AI deployment, Scale covers the entire AI lifecycle.
- **Research leadership**: In‑house Safety, Evaluation and Alignment Lab; co‑creator of the “Humanity's Last Exam” benchmark.

## Strategic Focus
- **Enterprise GenAI agents**: Ramping up “AgentOps” and “Frontier Agents” engineering teams (many open roles in SF, NY, London, Budapest).
- **Healthcare & life sciences**: Hiring dedicated GTM leaders and AI strategists for healthcare vertical.
- **International expansion**: Growing offices in London, Budapest, Mexico City, and Washington DC.
- **Safety and alignment**: Continued investment in red‑teaming, model evaluations, and government‑focused AI safety contracts.

## Why Work Here
- **Mission‑driven**: “Develop reliable AI systems for the world’s most important decisions” – directly shaping frontier AI capabilities.
- **Compensation & benefits**: Comprehensive health, dental, vision, mental health services; generous PTO; annual learning & development stipend; parental leave; ERGs; guest‑friendly offices with happy hours, game nights, book clubs.
- **Engineering culture**: Credos such as “Write the Market,” “Find the 20%,” “Earn Customer Love,” and “Quality is Our Cheat Code” emphasize impact over effort, customer obsession, and structured thinking.
- **Growth trajectory**: Rapid headcount growth (+32%), major Meta investment, and expansion into new verticals signal a company in high‑growth mode.
- **Flexible work**: Offices in SF, NY, London, Budapest, Mexico City, DC; the careers page highlights “flexible environment,” though specific remote/hybrid policy is not explicitly stated.

## Sources
1. [scale.com](https://scale.com/about)
2. [scale.com](https://scale.com/)
3. [scale.com/careers](https://scale.com/careers)
4. [linkedin.com](https://www.linkedin.com/company/scaleai)
5. [greenhouse.io](https://job-boards.greenhouse.io/scaleai)

## Other roles at Scale AI

- [Engineering Manager, Connectivity](https://feeny.ai/job/engineering-manager-connectivity-scale-ai-san-francisco-4164x0xvepes) — San Francisco, CA / New York, NY
- [Software Engineering Intern (Summer 2027)](https://feeny.ai/job/software-engineering-intern-summer-2027-scale-ai-doha-dan4rwykjkwb) — Doha, Qatar
- [Software Engineering Intern (Summer 2027)](https://feeny.ai/job/software-engineering-intern-summer-2027-scale-ai-london-y8rd2n7qqg8w) — London, United Kingdom
- [Software Engineer - New Grad](https://feeny.ai/job/software-engineer-new-grad-scale-ai-london-vzmr2pqdbnxk) — London, United Kingdom
- [Software Engineer - New Grad](https://feeny.ai/job/software-engineer-new-grad-scale-ai-doha-htj4304njmap) — Doha, Qatar
- [Staff Full-Stack Software Engineer, (Forward Deployed), GPS](https://feeny.ai/job/staff-full-stack-software-engineer-forward-deployed-gps-scale-ai-riyadh-23wvtk2r2609) — Riyadh, Saudi Arabia
- [Senior Full-Stack Software Engineer, (Forward deployed), GPS](https://feeny.ai/job/senior-full-stack-software-engineer-forward-deployed-gps-scale-ai-riyadh-erdv9vdxa2ej) — Riyadh, Saudi Arabia
- [Technical Program Manager (Cyber), Public Sector](https://feeny.ai/job/technical-program-manager-cyber-public-sector-scale-ai-columbia-309aqc75ajna) — Columbia, MD / Washington, DC
- [Director of Product Management, Enterprise Core Platform](https://feeny.ai/job/director-of-product-management-enterprise-core-platform-scale-ai-san-francisco-saj76g63zph3) — San Francisco, CA / New York, NY
- [Engineering Manager, Frontier AI Infrastructure - Public Sector](https://feeny.ai/job/engineering-manager-frontier-ai-infrastructure-public-sector-scale-ai-washington-gbg5965ts49g) — Washington, DC