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Mercury

3 days ago

Senior Machine Learning Operations Engineer

Remote · San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States

pythontypescriptreactsqlrediskafkaflaskfastapi

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AI TL;DR

You will build and operate the real-time inference service for risk decisioning at Mercury. This role involves managing model deployment infrastructure and ensuring high availability and low latency for production models.

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  1. What would you ship in the first month as Senior Machine Learning Operations Engineer at Mercury?
  2. Which tradeoff in the description would you ask about first?
  3. How do you explain a production incident to this team?
  4. What would you measure in the first two weeks?
  5. Which part of your last project maps to this stack?

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Job description

You will build and operate the real-time inference service for risk decisioning at Mercury. This role involves managing model deployment infrastructure and ensuring high availability and low latency for production models.

Details

  • San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States
  • $166,600—$208,300 USD for US employees
  • 5+ years in machine learning engineering or related field
  • Skills: Python, FastAPI, Flask, SQL, Redis, Kafka

The work

  • Build and operate the real-time inference service for scoring models
  • Own model deployment infrastructure including CI/CD and versioning
  • Implement model observability and monitoring for production services
  • Partner with Risk Data Science for model handoff and production operation