Develop and execute a strategic vision for our ML training platform, ensuring scalability, reliability, and performance to support large-scale Foundation and RL models.
Lead the design, implementation, and operation of a robust and efficient ML training platform to enable the training, experimentation, validation, and monitoring of ML models.
Attract, hire, and inspire a diverse world-class engineering team, fostering a culture of innovation, collaboration, and excellence.
Collaborate closely with cross-functional teams, including ML researchers, software engineers, data engineers, and hardware engineers to define requirements and align on architectural decisions.
Enable the engineers in the team to grow their careers by providing the right opportunities along with clear and timely feedback.

Requirements

10+ years of relevant experience, including 4+ years of management experience managing other managers and engineers.
Experience building user-friendly ML Infrastructure that enabled large-scale model training and high-throughput, low-latency serving use cases.
Experience with training frameworks like PyTorch, JAX, etc., leveraging GPUs for distributed model training.
Experience with GPU-accelerated inference using TensorRT, Ray Serve, or similar frameworks.

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
long-term and short-term disability insurance
life insurance

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningML training platformmodel trainingPyTorchJAXGPU-accelerated inferenceTensorRTRay Servedistributed model traininghigh-throughput serving

Soft Skills

leadershipcollaborationinnovationteam buildingmentoringcommunicationfeedbackculture of excellencestrategic visioninspiration