Engineering Manager, ML Performance Optimization

📋 Description

• Develop and execute a strategic vision and roadmap for ML Training and Inference Performance
• Lead the design, implementation, and operation of a robust and efficient ML platform to enable the
• Drive end-to-end performance optimization for large-scale model training and inference, including
• Attract, hire, and inspire a diverse world-class engineering team, fostering a culture of
• Collaborate closely with cross-functional teams, including ML researchers, software engineers, data
• Enable engineers on the team to grow their careers by providing the right opportunities and clear

🎯 Requirements

• 8+ years of relevant experience, including 3+ years of management experience managing engineers.
• Strong technical background in ML performance optimization, such as distributed training strategies
• Experience building user-friendly ML Infrastructure that enabled large-scale model training and
• Experience with training frameworks like PyTorch, JAX, etc., leveraging GPUs for distributed model
• Experience with GPU-accelerated inference using TensorRT, Ray Serve, or similar frameworks.
• Proven track record of extensive cross-functional collaboration, partnering with research, product

🎁 Benefits

• Paid time off (e.g. sick leave, vacation, bereavement)
• Unpaid time off
• Zoox Stock Appreciation Rights
• Amazon RSUs
• Health insurance
• Long-term care insurance