Technical Lead Manager, Machine Learning Runtime & Serving (AI)

TL;DR

Technical Lead Manager, Machine Learning Runtime & Serving (AI): Leading the technical vision and management of core ML infrastructure for autonomous driving with an accent on in-vehicle inference engines and cloud-based serving. Focus on architecting high-performance runtime systems across edge compute and large-scale data centers, and transitioning workloads to JAX-native architectures.

Location: Onsite in Mountain View, California

Salary: $251,000—$310,000 USD

Company

Waymo is an autonomous driving technology company building the World's Most Experienced Driver™ to improve mobility and safety.

What you will do

• Lead and grow a high-performing team of 6 engineers delivering the next-generation ML ecosystem.
• Architect scalable, high-performance ML runtime systems for both constrained edge compute (vehicles) and cloud data centers.
• Manage engineering trade-offs between real-time latency/memory limits for onboard execution and high-throughput cloud serving.
• Spearhead the transition of core ML workloads to a JAX-native runtime architecture, modifying ML compilers and runtimes.
• Collaborate with ML researchers in Perception and Planning to implement hardware-aware compute optimizations.
• Design advanced profiling and benchmarking infrastructure to eliminate bottlenecks across the end-to-end ML stack.

Requirements

• 8+ years of professional software engineering experience building and scaling complex ML systems.
• Proven track record in people management, including recruiting and mentoring senior engineers.
• Expertise in optimizing ML software for hardware accelerators like GPUs, TPUs, or custom silicon.
• Hands-on experience developing low-latency, fault-tolerant distributed backend systems at scale.
• B.S. or M.S. in CS, EE, Deep Learning, or a related field.

Nice to have

• PhD in CS, EE, or Deep Learning.
• Expertise in modifying ML compilers and inference engines (e.g., OpenXLA, TensorRT, ONNX Runtime, TVM).
• Background in building and scaling LLM serving systems using distributed inference techniques.
• Deep expertise in edge computing and automotive ML deployment under strict power and thermal constraints.

Culture & Benefits

• Participation in a discretionary annual bonus program.
• Equity incentive plan.
• Generous comprehensive company benefits program.