Staff Software Engineer, Compute Reliability
Company websitewaymo.com (Waymo, opens in new tab)
Base salary $251K to $310K
Employer-published annual base salary, USD. Advertised base range in Mountain View, CA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationMountain View, CA
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (1 h ago) · observed since
About this job
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
The Planner/Perception Reliability team’s goal is to build out architectures, tools, and workflows to prevent, identify, and guide fixes of reliability and software integrity issues.
We focus the organization on reliability and are accountable for the onboard software health while enabling high development velocity.
In this hybrid role you will report to a Tech Lead Manager.
You will:
- Drive the design and development of instrumentation and onboard architecture to proactively prevent, detect, and debug reliability issues across current and future Waymo compute platforms.
- Design and implement long-term strategies to systematically mitigate compute hardware reliability and numerical stability issues across heterogeneous platforms (CPU, TPU, GPU), creating scalable tools to automate triage, debugging, and resolution.
- Lead cross-functional initiatives across Waymo, Alphabet, and external partners to architect proactive solutions that prevent issues originating from compilers (LLVM, XLA, JAX), optimization (AutoFDO), or model changes.
- Architect frameworks and diagnostics to proactively identify and eliminate complex software and firmware faults, including deadlocks, memory corruption, race conditions, memory leaks, or tail latency spikes.
- Influence the design and tooling of next-generation hardware platforms, serving as a technical authority to ensure a coherent, forward-looking reliability architecture.
You have:
- BS/MS in Comp Sci, EE, Robotics, Physics, Math, or related field (or equivalent experience).
- Experience in C++.
- Experience with CUDA/GPU/TPU acceleration and model reliability or optimization.
- Experience with writing GPU kernels and evaluation/debugging of GPU workloads.
We prefer:
- MS or PhD in Computer Science, Robotics, similar technical field of study, or equivalent practical experience.
- Experience with autonomous vehicles (L4) or ADAS systems (L2/L3).
- Experience in software reliability space.
The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.
Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.
Salary Range
$251,000—$310,000 USD
Source: Waymo on Greenhouse · View original posting (opens in new tab)
Pay in context
This role's base floor ($251,000) is above 90% of the 4,664 Software Engineering roles in California listed on this site; 18 others list the same floor. Their median floor is $176,500; the middle half runs from $149,100 to $204,000.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 7, 2026.
This listingStaff Software Engineer, Compute Reliability$251K to $310K
Staff Machine Learning Engineer, Data Flywheel$250,000 to $334,530
Staff Tech Lead Software Engineer, Vehicle Realism Platform$251K to $310K
Staff Research Scientist, Foundation Models Recipes$251K to $310K
Senior Data Engineer$251K to $310K
Staff Machine Learning Engineer, AI Infrastructure$251K to $310K
Staff Software Engineer / Technical Lead Manager$251K to $319K
Chart as a table
| Role | Published base |
|---|---|
| Staff Software Engineer, Compute Reliability (this listing) | $251K - $310K |
| Staff Machine Learning Engineer, Data Flywheel | $250,000 - $334,530 |
| Staff Tech Lead Software Engineer, Vehicle Realism Platform | $251K - $310K |
| Staff Research Scientist, Foundation Models Recipes | $251K - $310K |
| Senior Data Engineer | $251K - $310K |
| Staff Machine Learning Engineer, AI Infrastructure | $251K - $310K |
| Staff Software Engineer / Technical Lead Manager | $251K - $319K |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2026-06-24
Where this pay comes from
Location as the employer wrote it: Mountain View, California, USA
$251,000—$310,000 USD
- Method
- Employer text, read with fixed rules and re-verified
- Checked
- Rule set
- us-base-v2
The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
