At Chase UK, we''re redefining digital banking by harnessing cutting-edge technology to deliver seamless, intuitive experiences for our customers. Our engineering team operates with a start-up mindset, empowered to shape the future of banking through scalable, reliable, and innovative solutions. If you''re passionate about operationalizing advanced machine learningincluding large language models (LLMs) and generative AIthis is the place for you.As a Mid-Level ML Engineer within the International Consumer Bank at JPMorgan Chase, you''ll work alongside ML scientists, Data Engineers and software engineers to build, deploy, and maintain sophisticated machine learning solutions in production. You''ll play a hands-on role in implementing ML pipelines, deploying models (including LLMs), and developing the supporting infrastructure that keeps our AI-driven products robust and scalable.Build, automate, and maintain ML pipelines for deploying advanced models, including large language models (LLMs), at scale.Collaborate with data engineers, scientists and product owners to operationalize workflows for reliable, seamless model deployment and monitoring.Implement monitoring, logging, and alerting for AI services, ensuring performance, security, and compliance in production environments.Write clean, maintainable, and efficient Python code for ML tooling, orchestration, and infrastructure.Docker, Kubernetes) to support scalable and repeatable deployments of AI services.Apply robust software engineering best practicesversion control, CI/CD, code reviews, testing, and automationto all aspects of the ML lifecycle.Troubleshoot and optimize ML workflows, from initial development through deployment and production support.Contribute to team growth by sharing knowledge and mentoring junior engineers as needed.Strong software engineering background, with deep proficiency in Python (and optionally, Go or Java).Familiarity with frameworks and tooling for LLMs and generative AI (e.g., Transformers, LangChain, Haystack, OpenAI, Vertex AI).Experience operationalizing ML solutions in cloud-native environments (AWS, GCP, Azure).Proficiency with containerization and orchestration (Docker, Kubernetes or similar) for scalable model deployment.Understanding of concurrency, distributed systems, and scalable API development for ML-powered applications.Experience working in agile, product-driven engineering teams.Exposure to Retrieval-Augmented Generation (RAG) pipelines, vector databases (e.g., Experience with advanced model monitoring, observability, and governance of LLMs and generative AI systems.Experience with data engineering or analytics platforms.Understanding of AI safety, security, and compliance best practices in production.Enthusiasm for learning and adopting the latest MLOps and AI technologies.#Morgan is a global leader in financial services, providing strategic advice and products to the world''s most prominent corporations, governments, wealthy individuals and institutional investors. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants'' and employees'' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing.