Senior ML Platform Engineer

1 week ago

City Of London, United Kingdom Bloomberg Full time

Location: London Business Area: Engineering and CTO Ref # 10047591 Description & Requirements Bloomberg’s Engineering AI department has 350+ AI practitioners building highly sought after products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will contribute to the team of Machine Learning (ML) and Software Engineers that are bringing innovative solutions to AI‑driven customer‑facing products. At Bloomberg, we believe in fostering a transparent and efficient financial marketplace. Our business is built on technology that makes news, research, financial data, and analytics on over 1 billion proprietary and third‑party data points published daily – across all asset classes – searchable, discoverable, and actionable. Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever‑increasing volume of structured and unstructured information needed to make informed decisions. Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most. We are looking for Senior ML Platform Engineers with strong expertise and passion for building platforms for (Gen) AI applications. As a Senior ML Platform Engineer, you will have the opportunity to create a more cohesive, integrated, and managed AI development life cycle to enable the building and maintenance of our AI systems. Our teams make extensive use of open source technologies such as Kubernetes, Kubeflow, KServe, Argo, Buildpacks, and other cloud‑native MLOps technologies. From technical governance to upstream collaboration, we are committed to enhancing the impact and sustainability of open source. Key Responsibilities Architect, build, and diagnose multi‑tenant AI platform systems Work closely with AI application teams to design seamless workflows for continuous model training, inference, and monitoring Collaborate with AI experts to understand workflows, pinpoint, and resolve inefficiencies, and inform the next set of features for the platforms Collaborate with open‑source communities and AI application teams to build a cohesive MLOps experience Design CI/CD automation frameworks that incorporate regulatory requirements Troubleshoot and debug user issues Provide operational and user‑facing documentation Required Qualifications Proven years of experience working with an object‑oriented programming language (Python, Go, etc.) Strong knowledge of Kubernetes, Argo, and container orchestration technologies Previous experience with modern CI/CD tools and GitOps workflows Familiarity with implementing automation for model development lifecycles A proactive mentality and ability to collaborate with peers, stakeholders, and management A degree in Computer Science, Engineering, Mathematics, or similar field of study or equivalent work experience An understanding of Computer Science fundamentals such as data structures and algorithms #J-18808-Ljbffr

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