Senior MLOps Engineer

Job Summary

A company is looking for a Senior ML Ops Engineer to manage the end-to-end ML lifecycle for a custom-built inference platform.

Key Responsibilities

• Build, maintain, and optimize production-grade ML pipelines for seamless transitions from experimentation to production
• Define and implement strategies for model versioning, rollout, rollback, and lifecycle management
• Collaborate cross-functionally to translate ML requirements into production-ready systems and influence technical planning

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field, or equivalent experience
• 5-8+ years of experience in Software Engineering, ML Engineering, Platform Engineering, or Infrastructure Engineering
• Hands-on experience deploying and maintaining LLMs and deep learning models in production environments
• Strong Python skills and familiarity with ML frameworks (PyTorch, TensorFlow or similar)
• Experience with cloud platforms such as AWS, GCP, or Azure, and familiarity with ML lifecycle tooling