Bring your passion for solving complex AI/ML engineering problems to a high impact role on our investment team. Through a close partnership with a team of portfolio managers and data scientists, your engineering expertise will contribute directly to the future growth and innovation of our products. As a Data Science Engineer in the Applied Data Science investment team within J.P. Morgan Asset Management, you will collaborate closely with portfolio managers and data scientists on a proprietary data science investment process. You will partner with team members across the full lifecycle of the team's AI/ML projects, helping to solve complex engineering problems from the research stage through to production implementation. Job Responsibilities: Design highly scalable pipelines for data ingestion and data processing Deploy efficient inference workflows for large-scale AI models Ensure pipeline robustness by constructing effective monitoring workflows Integrate datasets across a wide variety of formats Remain up to date with the latest developments in AI through research and experimentation Partner directly with the team's data scientists to facilitate research projects and production implementation Required Qualifications, Capabilities, and Skills: 3 years of relevant experience working with large-scale datasets Proficiency in programming languages such as Python Strong understanding of data science pipelines and relevant technologies Hands-on experience with public cloud services Intellectual curiosity and passion for problem solving Preferred Qualifications, Capabilities, and Skills: Demonstrated success bringing large-scale pipelines from research to production Experience working with AWS services Solid understanding of AI/ML models, including previous experience with deep learning frameworks Experience working with a variety of data formats, including natural language, image, and time series data