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Senior MLOps Engineer - job 1 of 7

Job Summary

A company is looking for a Senior MLOps Engineer.

Key Responsibilities
  • Design and implement GPU optimization strategies for ML workloads
  • Develop and maintain distributed training pipelines using the Ray framework
  • Manage and optimize ML infrastructure across multi-cloud environments
Required Qualifications
  • 5+ years of ML infrastructure experience, with 3+ years in GPU optimization
  • Hands-on experience with AWS/EKS for ML workloads
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field
  • Proven expertise with the Ray framework for distributed ML computing
  • Strong CUDA programming skills for GPU performance optimization

Average salary estimate

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SENIORITY LEVEL REQUIREMENT
TEAM SIZE
No info
EMPLOYMENT TYPE
Full-time, remote
DATE POSTED
August 15, 2025

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