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!