Faculty (faculty.ai) Logo

Faculty (faculty.ai)

Machine Learning Engineer

Reposted 20 Days Ago
Remote or Hybrid
Hiring Remotely in UK
Mid level
Remote or Hybrid
Hiring Remotely in UK
Mid level
The role involves designing, building, and deploying ML systems, supporting stakeholders, and operationalizing AI applications in Defence.
The summary above was generated by AI
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 Defence team is focused on building and embedding human-centered AI solutions which give our nation a competitive edge in the defence sector. We collaborate with our clients to bring ethical, reliable and cutting-edge AI to high-stakes situations and maintain the balance of global powers essential to our liberty.
Because of the nature of the work we do with our Defence clients, you will need to be eligible for UK Security Clearance (SC) and willing to work between 2 to 4 days per week on-site with these customers which may require travel to locations throughout the UK.
When not required on client sites, you’ll have the flexibility to work from our London office or remotely from elsewhere within the UK.

#LI-PRIO

About the role

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

You will be instrumental in bringing machine learning out of the lab and into the real world, contributing to scalable software architecture and defining best practices. Working with clients, and cross-functional teams, you'll ensure technical feasibility and timely delivery of high-quality, production-grade ML systems.

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.

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

  • 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'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)

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.

Some of our standout benefits:

  • Unlimited Annual Leave Policy

  • Private healthcare and dental

  • Enhanced parental leave

  • Family-Friendly Flexibility & Flexible working

  • Sanctus Coaching

  • Hybrid Working

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.

Similar Jobs

Yesterday
Remote or Hybrid
United Kingdom
Senior level
Senior level
Artificial Intelligence • Fintech • Software • Financial Services
Lead implementation of production-grade ML systems: data pipelines, training/evaluation workflows, scalable GPU inference, model fine-tuning (LoRA/QLoRA/SFT/DPO), deployment, and monitoring. Collaborate with product and application teams to ship reliable, efficient, and safe ML-powered features for real users while managing latency, cost, and robustness constraints.
Top Skills: DistillationDpoGpu-Based Training And Inference SystemsJaxLoraPythonPyTorchQloraSft
2 Days Ago
Remote
United Kingdom
Expert/Leader
Expert/Leader
Insurance
Lead and own ML platform end-to-end: data/feature pipelines, training and inference infrastructure, model registry, deployment, monitoring, and agentic AI stack. Design integrations across teams and third parties, ensure reproducibility, reliability, cost control, governance and audit trails, and grow a small engineering function supporting data scientists.
Top Skills: Agentic AiCachingCi/CdContainersFeature StoreInfrastructure As CodeLlmsModel RegistryOrchestrationPythonRetrievalSQL
11 Days Ago
Remote or Hybrid
UK
Expert/Leader
Expert/Leader
Artificial Intelligence • Machine Learning • Big Data Analytics
Lead technical authority for machine learning systems in the Defence domain. Define architectures, functional and non-functional requirements, solve cross-project technical challenges, guide strategy, mentor engineers, and deliver scalable AI solutions for high-stakes clients requiring UK security eligibility and regular on-site presence.

What you need to know about the Bristol Tech Scene

Along with Gloucester, Swindon and Bath, Bristol is part of the "Silicon Gorge" tech hub, a region in the U.K. renowned for its high-tech and research-driven industries, with a particular emphasis on sustainability and reducing environmental impact. As the European Green Capital, Bristol is home to 25,000 cleantech companies, including Baker Hughes and unicorn Ovo Energy. The city has committed to achieving net-zero emissions within the next decade.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account