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Faculty

Software Engineer (Safety)

  • Hybrid

Salary

Not stated

Similar roles pay £90K - 130K a year · our estimate

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Description

Why Faculty?

We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here .

We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.

Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.

AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen.

Our National Security and AI Safety business unit is dedicated to advancing the responsible development and deployment of AI in support of national security and global stability. From strengthening mission-critical capabilities across national security and intelligence, to working with frontier labs to provide robust AI safety red teaming and evaluation, we work at the frontier of high-stakes, high-impact missions.

We understand that powerful AI systems bring both transformative opportunities and complex risks and we are proud to partner with Government and the biggest tech organisations in the world to ensure AI is not just transformative but is also secure, trustworthy and safe for all.

About the role

Join us as a Software Engineer to deliver bespoke, impactful AI solutions for our diverse clients.

You will bridge the gap between AI research and real-world impact by building scalable, production-grade machine learning systems. Partnering with clients and cross-functional teams, you will champion technical feasibility, ensure seamless delivery, and collaborate with Frontier Labs to reinforce our leadership in practical, high-stakes AI safety.

What you'll be doing:

Building and deploying production-grade ML software, tools, and infrastructure.

Creating reusable, scalable solutions that accelerate the delivery of ML systems and capability testing of Frontier AI models.

Collaborating with engineers, data scientists, and commercial leads to solve critical client challenges.

Leading technical scoping and architectural decisions to ensure project feasibility and impact.

Defining and implementing Faculty’s standards for deploying machine learning at scale.

Acting as a technical advisor to customers and partners, translating complex ML concepts for stakeholders.

Who we're looking for:

You are comfortable building LLM applications, and are familiar with multi-agent harness tooling and AI Safety evaluation procedures.

You possess strong Python skills and solid experience in software engineering best practices.

You bring hands-on experience with cloud platforms and infrastructure (e.g., AWS, Azure, GCP), including architecture and security.

You've worked with container and orchestration tools such at Docker & Kubernetes to build and manage applications at scale

You are comfortable with core ML concepts, including probability, statistics, and common learning techniques.

You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch.

You're an excellent communicator, able to guide technical teams and confidently advise non-technical stakeholders.

You thrive in a fast-paced environment, and enjoy the autonomy to own scope, solve and delivery solutions

Where you’d work

Part of the week in the office

You can work from

  • United Kingdom

About the company

Faculty

  • Industry: AI

Office in London, United Kingdom

Your chances

Worth a look before you spend an evening tailoring a CV for it.

  • 19 checks run
  • 2 red flags

Still hiring?

13 checks

1 red flag

How crowded?

6 checks

1 red flag

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Details11 facts · Role, Location, Compensation, Employment, Company
Tech stack
  • Python
  • AWS
  • Kubernetes
  • Docker
  • PyTorch
  • Azure
  • LLMs
Type
Full-time
Industry
AI
Specialty
Backend
Region
United Kingdom
Pay period
Annual
Show 5 more factsShow less

Role

Category
Development
Specialty
Backend
Tech stack
  • Python
  • AWS
  • Kubernetes
  • Docker
  • PyTorch
  • Azure
  • LLMs

Location

Work model
Hybrid
Region
United Kingdom
Office
  • London, United Kingdom
Remote from
  • United Kingdom

Compensation

Salary
Salary by agreement
Pay period
Annual

Employment

Type
Full-time

Company

Industry
AI

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