ML Ops Engineering Lead

Job Purpose CIBC Global Markets Technology develops a diverse range of software and platforms to support CIBCs trading activities. These include systems for managing the risk of the derivatives book leveraging data science and machine learning and the development of front-end systems used by the business. We have made a substantial investment in building a robust data platform centred around Databricks which now captures extensive data flows across all aspects of our business. Role Overview In this role you will serve as an MLOps Engineer leading the development of a platform designed to empower users both within and beyond technology teams to build and deploy AI systems effectively. You will collaborate closely with the Quant Solutions Group which delivers quantitative and AI-driven solutions to Capital Markets as well as with developers from trading and sales teams. As an exceptional engineer you will bring significant expertise in Python and demonstrate a deep understanding of machine learning practices from an engineering perspective. You will excel at designing tools and systems that enable others to streamline their ML development and deployment processes and be a thought leader in MLOps. Key Accountabilities Lead the development of AI / ML CI / CD pipelines and frameworks to support AI / ML and Data Science solutions on the Azure Databricks platform. Define and implement systems to manage the full AI / ML lifecycle including data models and monitoring from both development and production perspectives. Collaborate with Data Scientists, sales and trading teams to build, monitor and maintain AI / ML solutions. Leverage the latest advancements in Generative AI and Large Language Model technologies and frameworks. Design and build systems that enable agentic workflows to be deployed driving automation and efficiency. Cross‑Functional Relationships This role will involve working closely with other technology partners as well as data scientists throughout the business. Compliance Requirements / Responsibilities As an employee of CIBC the incumbent must comply with all applicable CIBC and Line of Business policies, standards, guidelines and controls. Authorities / Decision Rights This role has the authority to make architectural decisions about the MLOps environment. This role has the authority to make changes to the devops environments used within the quant group. Knowledge and Skills Above all we are looking for a top class ML ops engineer with excellent interpersonal skills. We want to hear from a wide range of applicants. Although individual candidates will come with diverse backgrounds the following specific attributes are a useful guide to the level of performance expected : A degree in Computer Science or related subject (or equivalent knowledge) 7 years of hands‑on experience building AI / ML systems 3 years of hands‑on MLOps experience Expert Python programmer Expert in devops platforms like GitHub Actions Deep knowledge of Databricks usage and APIs Experience in working with Kubernetes ideally AKS Experience in infrastructure‑as‑code A solid practical understanding of AI / ML models and algorithms LLMs agentic AI and the platforms used to build them A solid understanding of databases Experience deploying agentic systems a plus Excellent interpersonal skills teamwork and communication. Highly motivated with a genuine passion for finding elegant and practical solutions to technical problems Working Conditions This role operates within a normal office environment with some scope for partial remote working. What you need to know CIBC is committed to creating an inclusive environment where all team members and clients feel like they belong. We seek applicants with a wide range of abilities and we provide an accessible candidate experience. If you need accommodation please contact You need to be legally eligible to work at the location(s) specified above and where applicable must have a valid work or study permit. Job Location 150 Cheapside London UK Employment Type Regular Weekly Hours 35 #J-18808-Ljbffr