Principal MLOps Engineer - Chase UK

Key Skills

Aartificial intelligence, Data science techniques, Design, Machine learning techniques, MLOps tools

Job Description

As a Principal MLOps Engineer at JPMorgan Chase within the International Consumer Bank, you provide deep engineering expertise and work across agile teams to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way . You are expected to be involved in the design and architecture of the solutions while also focusing on the entire SDLC lifecycle stages.

Our Machine Learning Operations team is at the heart of this venture, focused on getting smart ideas into the hands of our customers. We're looking for people who have a curious mindset, thrive in collaborative squads, and are passionate about new technology. By their nature, our people are also solution-oriented, commercially savvy and have a head for fintech. We work in tribes and squads that focus on specific products and projects – and depending on your strengths and interests, you'll have the opportunity to move between them.

Job responsibilities:

• Advise and leads development of tooling for AI/ML development and deployment.
• Lead deployment and maintenance of infrastructure, model monitoring and observability tools, providing an effective model development platform for data scientists and ML engineers.
• Collaborate with machine learning model developers to bring ML models to production.
• Mentor and leads a team of engineers focused on deploying machine learning pipelines at scale.
• Partner with product, architecture, and other engineering teams to define scalable and performant technical solutions.
• Influence across business, product, and technology teams and successfully manages senior stakeholder relationships
• Champion the firm’s culture of diversity, equity, inclusion, and respect.

Required qualifications, capabilities and skills

• Formal training or certification on software engineering concepts and MLOps applied experience.
• Experience with machine learning engineering and operations in a large enterprise.
• Experience in building, evaluating and deploying ML models into production
• Experience leading complex projects supporting system design, testing and operational stability.
• Demonstrated prior experience influencing across complex organizations and delivering value at scale.
• Extensive practical cloud native experience
• Proven expertise on adoption of agile practices to deliver efficiently and to the expected quality solutions.