Faculty (faculty.ai) Logo

Faculty (faculty.ai)

Lead Machine Learning Engineer

Posted Yesterday
Be an Early Applicant
Hybrid
London, England
Expert/Leader
Hybrid
London, England
Expert/Leader
Lead the technical direction and delivery of complex machine learning platforms in high-risk environments. Design scalable production ML systems, deployment infrastructure, APIs, testing frameworks, model versioning, and CI/CD pipelines. Define architecture and technical roadmaps, oversee multiple workstreams, guide technology adoption, and manage and coach engineers. The role requires expertise in cloud-native ecosystems, Kubernetes, TensorFlow or PyTorch, agentic systems, and production model operations.
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 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.
Because of the nature of the work we do with our Government clients, you may need to be eligible for UK Developed Vetting (DV) and willing to work on site with our clients from time to time.

 
About the role
 

As a Lead Machine Learning Engineer at Faculty, you will set the technical direction for complex AI/ML projects, ensuring models perform at scale and in production over time by balancing technical trade-offs and guiding team priorities.

 

You will lead the delivery of large-scale AI-powered platforms in high-risk environments while defining project roadmaps across multiple complex workstreams.


This is an ambitious, entrepreneurial leadership role where you will act as a trusted technical expert, defending your architectural rationale to senior stakeholders to ensure we deliver high-quality, high-value outputs.

 
 
What you'll be doing:
 
  • Designing, implementing, and maintaining reliable, scalable ML systems while justifying key architectural decisions for production environments.

  • Driving the development of shared libraries and infrastructure for model deployment, lifecycle management, and CI/CD pipelines.

  • Leading model integration with infrastructure by creating APIs and services that enable scalable AI functionality in applications.

  • Overseeing the delivery of multiple complex workstreams and defining project problems in high-risk environments.

  • Ensuring reliable model performance by defining testing frameworks and model versioning systems for senior engineers to implement.

  • Managing and coaching multiple individuals, setting team-wide development goals to improve technical depth and client delivery.

  • Executing proactive recommendations for adopting new technologies and AI frameworks to maintain Faculty's competitive market position.

 
 
Who we're looking for:
 
  • You are an expert at defining technical roadmaps and managing project priorities to deliver high-stakes outcomes within high-growth environments.

  • You possess mastery of cloud-native ecosystems and orchestration tools like Kubernetes to automate complex model lifecycles and robust CI/CD pipelines.

  • You have a proven ability to design large-scale, AI-powered platforms and provide the technical justification for critical architectural decisions in high-risk environments.

  • You bring expert-level experience in operationalising models within frameworks like TensorFlow or PyTorch to solve complex, high-impact business challenges.

  • You define the engineering standards and architecture patterns for agentic systems, ensuring teams build to a consistent, production-grade bar.

  • You demonstrate an exceptional ability to align multi-disciplinary technical teams with broader business objectives and evolving customer needs.

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

  2. Introduction to the Hiring Manager (30 minutes)

  3. Pair Programming Interview (90 minutes)

  4. System Design Interview (90 minutes)

  5. Commercial & Leadership 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.

Similar Jobs

26 Days Ago
In-Office
Entry level
Entry level
Artificial Intelligence • Machine Learning • Big Data Analytics
Lead the technical direction and delivery of complex machine learning and software projects. Architect scalable production systems, define roadmaps, manage high-risk workstreams, develop reusable libraries, mentor and hire engineers, evaluate technologies, estimate work, and advise customers and stakeholders. The role combines advanced software and ML engineering with team leadership, technical coaching, client delivery, and solution architecture.
Top Skills: Amazon Web ServicesAzureDockerGoGoogle Cloud PlatformJavaKubernetesMachine LearningPythonRustTypescript
26 Days Ago
Remote or Hybrid
United Kingdom
Entry level
Entry level
Artificial Intelligence • Fintech • Software • Financial Services
Lead end-to-end machine learning systems across data, training, fine-tuning, evaluation, inference, deployment, and monitoring. Build scalable GPU-based infrastructure and reliable production pipelines for large models, optimize performance and cost, and partner with research and application engineering to translate model capabilities into product improvements. Provide hands-on technical leadership, resolve production issues, and ensure measurable, safe, and maintainable ML iterations.
Top Skills: Gpu-Based Training And Inference SystemsJaxPythonPyTorch
One Month Ago
Hybrid
Senior level
Senior level
Financial Services
Lead design, develop, and deliver cloud-based applications and services; integrate AI/ML models and LLM APIs; promote and operationalize AI-assisted engineering practices; ensure performance, scalability, security, and automation; mentor peers, conduct code reviews, and drive reuse and resiliency across the software development lifecycle.
Top Skills: Ai-Assisted Development ToolsAWSAzureBedrockCi/CdCloud-Native DatabasesDockerEvent-Driven ArchitecturesGenerative AiGoogle Cloud PlatformInfrastructure As CodeJavaKubernetesLlm ApisNoSQLOpenaiPrompt EngineeringPythonRestful ApisServerless ArchitecturesSQLTerraform

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