Machine Learning Platform Engineer

Bonhill Partners
London
3 months ago
Applications closed

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Platform Engineer, Machine Learning

Platform Engineer, Machine Learning

Staff Machine Learning Platform/Ops Engineer Location: London

Staff Machine Learning Platform/Ops Engineer

Machine Learning Engineer

Machine Learning Engineering Lead

Bonhill Partners are supporting a leading Systematic Trading firm in London as they grow their AI/ML Solutions division. The organisation is seeking a Machine Learning Platform Engineer to build and scale the next generation of MLOps and ML engineering capabilities across the business. This is a greenfield role, offering significant influence over tooling, standards, and best practices.

The position blends hands-on engineering with enablement: you will design and deploy automation pipelines, enhance ML development environments, and upskill internal teams on modern software and MLOps practices.


Key Responsibilities

  • Design, deploy, and refine automation and CI/CD workflows to support machine learning and data pipelines
  • Build scalable MLOps frameworks and champion best practices across DataOps, ModelOps, and ML lifecycle management
  • Educate and mentor Researchers and Developers on clean code, software architecture, and reproducible ML practices
  • Deliver training on consistent development environments, modern tooling, and AI-assisted engineering workflows
  • Support internal events such as hackathons, coding challenges, and engineering workshops
  • Maintain and contribute to internal training repositories, documentation, and shared platform components
  • Collaborate with cross-functional engineering and data teams to expand platform capabilities and improve reliability
  • Engineer cloud-based solutions leveraging containerisation and infrastructure-as-code to support scalable ML systems


Skills & Experience

  • Strong programming background in Python (and/or C++)
  • Proven experience with CI/CD systems, Git workflows, and infrastructure-as-code tooling
  • Hands-on expertise with Azure Databricks and cloud-native technologies (Docker, Kubernetes, Terraform)
  • Solid understanding of MLOps concepts and tooling (MLflow, Airflow etc.); exposure to LLMOps is advantageous
  • Experience working with Generative AI / LLMs, and familiarity with AI engineering agents (e.g., Cursor, Claude Code, Codex)
  • Strong SQL capability and proven experience delivering robust ML engineering solutions
  • Excellent communication skills with a collaborative mindset focused on enabling and uplifting technical teams
  • An interest in teaching, improving engineering standards, and contributing to a strong internal engineering culture
  • Financial services or trading environment experience is beneficial but not essential


We look forward to hearing from you!

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