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Machine Learning Engineer (Safety)

Faculty· Engineering
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Hybrid (London)Full-timePosted 1mo ago

About the role

Join Faculty as a Machine Learning Engineer to deliver bespoke, impactful AI solutions for diverse clients. Bridge the gap between AI research and real-world impact by building scalable, production-grade ML systems, collaborating with clients and cross-functional teams, and reinforcing leadership in practical AI safety.

Responsibilities

  • 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.

Qualifications

  • 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

Skills

Required:LLM applicationsMulti-agent harness toolingAI Safety evaluationPythonCloud platformsDocker & KubernetesML lifecycle
Last updated Oct 21, 2026. Interested? Apply on the company site.
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Faculty partners with organisations to enhance performance through cutting-edge artificial intelligence solutions, driving real-world impact.

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