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Remote Senior Machine Learning Operations Engineer

at Mercury

Posted 1 month ago

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Description:

  • Build and operate a real-time inference service for risk decisioning with low latency and high availability.
  • Own model deployment infrastructure including registry, CI/CD, and performance checks.
  • Develop model observability features such as monitoring and drift detection.
  • Collaborate with Risk Data Science for model handoff and production operation.
  • Implement experimentation capabilities and explainability outputs.
  • Take ownership of product development and contribute to building a new platform team.

Requirements:

  • 5+ years in machine learning engineering, backend software engineering, or MLOps.
  • Experience in deploying and operating production ML services in low-latency contexts.
  • Strong backend engineering skills in Python with API frameworks like FastAPI or Flask.
  • Familiarity with model deployment tools, CI/CD, and versioning.
  • Experience in building observability and alerting for production services.
  • Knowledge of SQL and low-latency data stores (e.g., Redis, DynamoDB).

Benefits:

  • Competitive base salary and equity (stock options/RSUs).
  • Salary range for US employees: $166,600 - $208,300 USD; for Canadian employees: $157,400 - $196,800 CAD.

Job title

Machine Learning Ops Engineer

Job type

Full-time

Experience level

Senior

Required experience

5 years

Salary

$166,600—$208,300 / year

Degree requirement

No degree required

Skills

TypeScript React.js SQL Redis Kafka AWS Software as a Service Dynamodb CI/CD Machine Learning Python Haskell Snowflake Flask FastAPI Apache Kafka Message queues Airflow

Location requirements

Canada United States

Benefits

Equity compensation Stock options Competitive salary

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