Senior Machine Learning Engineer, AI Platform

What you'll do

• Own the architecture and roadmap for major ML compute and inference platform components.
• Design and operate distributed systems for large-scale training and low-latency inference across thousands of accelerators.
• Drive multi-tenancy, elasticity, and cost efficiency across a shared GPU fleet.
• Build automated paths to move models from experiment to production without re-implementation.
• Set engineering standards for reliability, observability, and performance across the platform.
• Partner with researchers to turn emerging workloads into first-class platform capabilities.
• Provide technical leadership and mentorship across the platform organization.

What we're looking for

• 7+ years of experience building and operating large-scale platform, infrastructure, or distributed systems in production.
• Deep expertise in distributed systems and cloud infrastructure, including Kubernetes and containerized workloads.
• Experience operating large multi-node and multi-region clusters.
• Strong programming ability in Python and at least one systems language such as Go, C++, Rust, or Java.
• Proven track record of designing systems that other engineers build on and taking them from design to production at scale.
• Experience with GPU or accelerator scheduling, performance tuning, or fleet management (preferred).
• Familiarity with ML framework internals, distributed training, or modern inference stacks (preferred).
• Experience operating ML or data infrastructure at the scale of a major ML-driven product organization (preferred).