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jpmc-dev6.fa.oraclecloud.com/CX

Machine Learning Engineer Vice President

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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

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