Machine Learning Engineering Manager

Key Responsibilities

• Act as a key leader in establishing excellence within machine learning engineering and across the detection team
• Line manage a team of machine learning engineers - providing coaching and guidance in support of the ongoing development and growth of your team
• Propose and champion new machine learning methods and tools (including platforms that empower Data Science experimentation) to influence the technical roadmap and promote continuous innovation
• Drive cross-functional initiatives with Data Engineering, Infra, and other teams to align on data architecture and ensure we make the right ML product decisions
• Investigate model performance issues
• Develop and deploy new models to detect fraud whilst maintaining SLAs

Skills, Knowledge and Expertise

• Minimum of 1 year of experience as an engineering manager, managing at least 3 people
• You are a strong collaborator with colleagues outside of your immediate team, for example with data science, engineering, product, client operations teams and with senior leadership
• You know how to manage and retain talented engineers from a diverse range of backgrounds and personalities. You can handle difficult management situations with tact, empathy and support
• You have significant experience building and deploying ML models using the Python data stack
• Familiarity with modern workflow orchestration tools such as Prefect, Kubeflow, Argo, etc.
• You understand software engineering best practices (version control, unit tests, code reviews, CI/CD) and how they apply to machine learning engineering
• Comfortable spending 30-40% of your time hands-on in the codebase and adapting your technical involvement based on the roadmap
• Pytorch or Tensorflow deep learning experience
• Experience with Go, C++, Java or another systems language
• Experience using dbt

Benefits