Software Engineer (Safety)

Posted 6 Days Ago
Be an Early Applicant
London, England, GBR
In-Office
Entry level
Artificial Intelligence • Machine Learning • Big Data Analytics
The Role
Build and deploy production-grade machine learning software, tools, and infrastructure for high-stakes AI safety and national security applications. The role involves creating scalable ML solutions, evaluating frontier AI models, making architectural decisions, advising clients, and collaborating with engineers, data scientists, commercial teams, and research labs. Candidates should have strong Python and software engineering skills, cloud and containerization experience, ML lifecycle knowledge, and familiarity with LLM applications and AI safety evaluation.
Summary Generated by Built In
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.

About the team
 

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

 
Our Interview Process
 
  1. Talent Team Screen (30 minutes)

  2. Pair Programming Interview (90 minutes)

  3. System Design Interview (90 minutes)

  4. Commercial Interview (60 minutes)

#LI-PRIO

 

Our Recruitment Ethos

We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.

If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.

A note on AI: we're happy for you to use it for research and interview prep, but please don't use it to generate answers during live interviews. We also use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of just let us know,) and every application is reviewed by a human, never decided by AI.

Skills Required

  • Experience building LLM applications and familiarity with multi-agent harness tooling and AI safety evaluation procedures
  • Strong Python skills and software engineering best practices
  • Hands-on experience with cloud platforms and infrastructure, including AWS, Azure, or GCP
  • Experience with cloud architecture and security
  • Experience with Docker and Kubernetes
  • Understanding of probability, statistics, and common machine learning techniques
  • Experience across the full machine learning lifecycle and operationalizing models
  • Experience with Scikit-learn, TensorFlow, or PyTorch
  • Strong communication skills and ability to advise non-technical stakeholders
  • Ability to work autonomously in a fast-paced environment and own solution delivery
Am I A Good Fit?
beta
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.

The Company
HQ: London
663 Employees
Year Founded: 2014

What We Do

We build and deploy safe AI systems that combine the best of human and artificial intelligence to help our customers achieve exceptional performance.

Similar Jobs

Elanco Logo Elanco

Lead Software Engineer

Healthtech • Pharmaceutical • Manufacturing
In-Office
Hook, East Riding of Yorkshire, England, GBR
8445 Employees

Faculty (faculty.ai) Logo Faculty (faculty.ai)

Senior Software Engineer

Artificial Intelligence • Machine Learning • Big Data Analytics
In-Office
London, England, GBR
663 Employees
In-Office or Remote
14 Locations
23 Employees
160K-180K Annually

Scarlet Logo Scarlet

Software Safety Engineer

Healthtech • Software
In-Office
London, Greater London, England, GBR
51 Employees

Similar Companies Hiring

Onshore Thumbnail
Artificial Intelligence • Fintech • Software • Financial Services
New York, New York
60 Employees
Blee Thumbnail
Artificial Intelligence • Marketing Tech • Software
New York, New York
30 Employees
Vega Thumbnail
Artificial Intelligence • Automotive • Insurance • Transportation
US
43 Employees

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account