Tech Stack

Description

You will lead the team responsible for evolving our AI/ML stack to support massive-scale production. You'll define the vision for MLOps, manage a team of engineers, and collaborate cross-functionally to build reliable infrastructure for ML training and inference.

Requirements

• Bachelor's/Master's in CS or related field or equivalent experience
• 2-3+ years managing engineering teams focused on MLOps or ML infrastructure
• Deep technical expertise with ML workloads on Kubernetes and cloud platforms (AWS/GCP/Azure)
• Proven experience managing petabyte-scale datasets and high-throughput inference pipelines
• Strong software engineering skills in multi-language systems and scalable architectures

Responsibilities

• Develop and execute long-term vision and roadmap for MLOps team
• Lead and mentor a team of 6-7+ high-performing engineers
• Partner with leaders across ML, data science, product engineering, and infrastructure
• Architect compute and storage pipelines for managing millions of slides
• Modernize AI product inference stack to support 5-10x growth