Staff MLOps Engineer

Job Summary

Focused on building and operating critical systems for AI models in production, the full-time Staff MLOps Engineer will design robust ML infrastructure, optimize model deployment, and implement CI/CD processes in a remote setting.

Key responsibilities

• Build ML infrastructure for low-latency model deployment and distributed inference pipelines
• Scale ranking systems by optimizing execution latency and cloud infrastructure costs
• Implement model CI/CD for automated versioning and zero-downtime rollbacks

Required qualifications

• 4-8+ years of experience in MLOps, Machine Learning Engineering, or distributed platform engineering
• Hands-on experience with ultra-low-latency machine learning model deployment
• Proficiency in Python and PyTorch
• Experience with cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes)
• Experience designing scalable data pipelines and automated CI/CD infrastructures