Senior MLOps Engineer

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