Equity ML Engineer - Asset Management (VP Level)

Testing Site - JPMC

New York (NY)

On-site

USD 120,000 - 180,000

Full time

14 days+

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Job summary

Testing Site - JPMC is seeking a skilled ML/Data Engineer to join the team responsible for building scalable data pipelines and AI/ML capabilities that support US Equity investment processes. The role focuses on end-to-end design from research to production, partnering with portfolio managers, data scientists, and ML engineers.

The candidate will implement data ingestion, inference services, and monitoring for large models, while ensuring cost efficiency and reliability in cloud environments.

Qualifications

  • 3+ years of relevant experience building large-scale data and modeling pipelines.
  • Strong proficiency in Python and experience working with REST APIs and OAuth workflows.
  • Advanced familiarity with cloud computing platforms (e.g., AWS, Google Cloud, Azure).
  • Intellectual curiosity and passion for problem solving.

Responsibilities

  • Implement scalable data ingestion and transformation pipelines for financial and alternative data.
  • Design, deploy, and operate inference services and monitoring for large models.
  • Contribute to robust workflows: experiment tracking, reproducibility, evaluation, and post-deployment monitoring.
  • Work closely with the portfolio management team to develop new investment capabilities.
  • Optimize cost, performance, and reliability in cloud environments.

Skills

Python
REST APIs
OAuth
Cloud platforms
Problem solving

Job description

Testing Site - JPMC is seeking a skilled ML/Data Engineer to join the team responsible for building scalable data pipelines and AI/ML capabilities that support US Equity investment processes. The role focuses on end-to-end design from research to production, partnering with portfolio managers, data scientists, and ML engineers.

The candidate will implement data ingestion, inference services, and monitoring for large models, while ensuring cost efficiency and reliability in cloud environments.

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