Technical Lead - ML Platform & MLOps

Requirements:

• 6+ years of strong hands-on software/platform engineering experience.
• Strong programming skills in Python.
• Deep hands-on experience with Kubernetes, containers and Linux.
• Experience building or operating large-scale distributed systems or platform infrastructure.
• Strong understanding of cloud infrastructure including compute, storage and networking.
• Experience building production-grade CI/CD and automation platforms.
• Experience with workflow orchestration such as Apache Airflow or equivalent systems.
• Experience with ML lifecycle tooling such as MLflow or equivalent platforms.
• Strong understanding of ML training and deployment workflows.
• Experience with Infrastructure as Code, preferably Terraform.
• Strong debugging and production troubleshooting skills.
• Experience building systems with monitoring, logging, metrics and alerting.
• Strong fundamentals in system design, reliability and distributed computing.

Strong Differentiators:

We would especially love to meet you if you have worked on:

• Ray or other distributed computing frameworks
• Distributed or multi-node ML training
• GPU and multi-GPU infrastructure
• Kubernetes-based ML platforms
• ML training platforms used by multiple teams
• Model serving and inference infrastructure
• GPU scheduling and utilisation optimisation
• Large-scale workflow orchestration
• ML platform developer experience
• Infrastructure cost and performance optimisation
• Feature platforms or feature stores