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Lead Machine Learning Engineer

Faculty· Engineering
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Hybrid (London)Full-timePosted 4mo ago

About the role

Lead ML Engineer responsible for setting technical direction for large-scale AI/ML projects, delivering production-ready AI-powered platforms in high-risk environments, and guiding multiple workstreams and teams.

Responsibilities

  • 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.

Qualifications

  • Expert at defining technical roadmaps and managing project priorities to deliver high-stakes outcomes within high-growth environments.
  • Mastery of cloud-native ecosystems and orchestration tools like Kubernetes to automate complex model lifecycles and robust CI/CD pipelines.
  • Proven ability to design large-scale, AI-powered platforms and provide the technical justification for critical architectural decisions in high-risk environments.
  • Expert-level experience in operationalising models within frameworks like TensorFlow or PyTorch to solve complex, high-impact business challenges.
  • Ability to define engineering standards and architecture patterns for agentic systems to ensure consistent production-grade outputs.
  • Exceptional ability to align multi-disciplinary technical teams with broader business objectives and evolving customer needs.

Skills

Required:Technical roadmappingCloud-native ecosystemsAI platform designModel operationalisation
Last updated Oct 21, 2026. Interested? Apply on the company site.
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