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Salary
$157k – $285k per year (Estimated)
Location
In office (London)
Seniority
Senior · 5+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Scale AI is an American company founded in San Francisco in 2016 that supplies the training data, evaluation and tooling behind large artificial intelligence systems. It began with human-labelled annotation for autonomous driving and computer vision, then expanded into reinforcement learning from human feedback, expert data generation, model evaluation and full-stack deployment platforms for enterprises and governments. In 2025 Meta acquired a large minority stake and hired co-founder Alexandr Wang, after which the company continued under new leadership serving defence, public sector and commercial customers.

Software is eating the world, but AI is eating software. We live in unprecedented times - AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition.

At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI.

At the foundation of these products is the Platform Engineering team.  In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems.  You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies.

You will:

  • Drive the design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements.
  • Collaborating with cross-functional teams to define, design, and deliver new features.
  • Proactively identifying opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades.
  • Presenting technical information to teams and stakeholders, providing guidance and insight on development processes and technologies.

Ideally you’d have:

  • 5+ years of full-time engineering experience, post-graduation with specialties in back-end systems, specifically related to building large-scale data storage, streaming, and warehousing systems.
  • Experience in various database technologies (MongoDB, Postgres), streaming/processing solutions (Kinesis, Flink, Spark), indexing/caching (ElasticSearch, Redis), and various data query engines (Trino, Presto, Snowflake, etc.).
  • Show a track record of mentoring and leading teams in successful projects.
  • Possess excellent communication and collaboration skills, and the ability to translate complex technical concepts to non-technical stakeholders.
  • Experience working fluently with standard containerization & deployment technologies like Kubernetes and various public cloud offerings.
  • Extensive experience in software development and a deep understanding of distributed systems, cloud platforms and data systems.

Nice to haves:

  • Strong knowledge of software engineering best practices and CI/CD tooling (CircleCI).
  • Experience scaling products at hyper-growth startups.
  • Excitement to work with AI technologies.

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 [email protected]. Please see the United States Department of Labor's Know Your Rights poster 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 for additional information.

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