---
title: 'Frontier Agents Engineer at Scale AI'
canonical: 'https://feeny.ai/job/frontier-agents-engineer-scale-ai-london-2wn20rsq2gmh'
type: 'job'
last_seen: '2026-09-09'
---

# Frontier Agents Engineer at Scale AI

- **Company:** Scale AI
- **Location:** London, United Kingdom
- **Posted:** 2025-03-05
- **Last confirmed live:** 2026-09-09
- **Apply:** https://job-boards.greenhouse.io/scaleai/jobs/4536659005

## Job description

AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the usage of frontier data and models by building complex agents for enterprises around the world through our Scale Generative Platform (SGP).

The SGP ML team works on the front lines of this AI revolution. We interface directly with clients to build cutting edge products using the arsenal of proprietary research and resources developed at Scale. As an Applied AI Engineer, you’ll work with clients to create ML solutions to satisfy their business needs. Your work will range from building next-generation AI cybersecurity firewalls to creating transformative AI experiences in journalism to applying foundation genomic models making predictions about life-saving drug proteins. Daily data-driven experiments will provide key insights around model strengths and inefficiencies which you’ll use to improve your product’s performance. If you are excited about shaping the future of the modern AI movement, we would love to hear from you!

You will:

- Own, plan, and optimize the AI behind our Enterprise customer’s deepest technical problems
- Leverage SGP to build the most advanced AI agents across the industry including multimodal functionality, tool-calling, and more
- Have experience gathering business requirements and translating them into technical solutions
- Meet regularly with customer teams onsite and virtually, collaborating cross-functionally with all teams responsible for their data and ML needs
- Push production code in multiple development environments, writing and debugging code directly in both our customer’s and Scale’s codebases
- Be able and willing to multi-task and learn new technologies quickly

Ideally you'd have:

- A love for solving deeply complex technical problems with ambiguity using state of the art research and AI to accomplish your client’s business goals
- Strong engineering background: a Bachelor’s degree in Computer Science, Mathematics, or another quantitative field or equivalent strong engineering background.
- Deep familiarity with a data-driven approach when iterating on machine learning models and how changes in datasets can influence model results
- Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
- Proficiency in Python to write, test and debug code using common libraries (ie numpy, pandas)

Nice to haves:

- Strong knowledge of software engineering best practices
- Have built applications taking advantage of Generative AI in real, production use cases
- Familiarity with state of the art LLMs and their strengths/weaknesses

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)

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