Waymo is an autonomous driving technology company with a mission to make it safe and easy for people and things to get where they’re going. Since our start as the Google Self-Driving Car Project in 2009, Waymo has been focused on building the Waymo Driver—The World’s Most Experienced Driver™—to improve everyone's access to mobility while saving thousands of lives now lost to traffic crashes. Our Waymo Driver powers Waymo One, our fully autonomous ride-hailing service, as well as Waymo Via, our trucking and local delivery service. To date, Waymo has driven over 20 million miles autonomously on public roads across 25 U.S. cities and conducted over 20 billion miles of simulation testing.
At Waymo, we are mission-driven and believe deeply in the opportunity of autonomous driving technology to improve mobility and make people's lives better. We are united by purpose and responsibility (for our employees and riders alike). We are looking for kind, committed, employees who have integrity, dream big, work together as one team and create a sense of belonging for one another that is the foundation of our culture. We want each team member to feel welcomed and included in every step of our exciting journey.
Waymo's Compute Team is tasked with a critical and exciting mission: We deliver the compute platform responsible for running the fully autonomous vehicle’s software stack. To achieve our mission, we architect and create high-performance custom silicon; we develop system-level compute architectures that push the boundaries of performance, power, and latency; and we collaborate closely with many other teammates to ensure we design and optimize hardware and software for maximum performance. We are a multidisciplinary team seeking curious and talented teammates to work on one of the world’s highest performance automotive compute platforms.
In this role, you'll:
- Architect, simulate and design amazing machine learning solutions for our autonomously driven vehicles
- Build scalable tools for modeling and performance evaluation
- Interact with cross-functional engineering teams to identify opportunities and requirements
- Architect machine learning solutions to best suit Waymo’s unique requirements
At a minimum we’d like you to have:
- BS degree in Computer Science or Computer Engineering or equivalent, or equivalent practical experience
- 3+ years on designing/architecting complex, high performance architectures
- 2+ years of experience with performance simulation and modeling in C++
- 2+ years of experience with CPUs, GPUs, memory systems, and accelerators
It's preferred if you have:
- 1+ years experience with machine learning architectures, acceleration and optimization
- Experience with SoC interconnects and NoCs
- Familiarity with SystemC, GEM5 simulation frameworks
- Familiarity with microarchitecture design & tradeoffs – power, performance, area
- Strong communication skills
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.
While at Waymo, you will enjoy benefits that cover…
Health and wellness: Our people are at the heart of everything we do. At Waymo, you can enjoy top-notch medical, dental and vision insurance, mental wellness support, a Flexible Spending Account (FSA), a Health Saving Account (HSA), on-site physicians and/or nurses in some locations, and special wellness programs.
Financial wellness: Your financial peace of mind is important to us. At Waymo, we offer competitive compensation, bonus opportunities, equity, a generous 401(k) plan or regional retirement plans, 1-on-1 financial coaching, a 529 College Savings Plan and lots of other perks and employee discounts.
Flexibility and time off: Take the time you need to relax and recharge. Enjoy the flexibility to work from another location for four weeks per year. We support an on-site, hybrid work model and offer remote working opportunities, paid time off, Waymo recharge days, bereavement, sick, and parental leave.
Supporting families: When it comes to growing your family or caring for your loved ones, you have our full support. Enhanced leave options include paid parental leave (birthing parent gets 24 weeks of paid leave, and non-birthing parent gets 18 weeks of paid leave), and 20 subsidized days of backup childcare or adult/elder care. Access to fertility care or adoption support as you grow your family.
Community and personal development: At Waymo, you’ll find a range of opportunities to grow, connect, and give back. We offer education tuition reimbursement, personal and professional development, mentorship, and other ways to connect through Employee Resource Groups (ERGs), other internal groups, and even time off to volunteer.
Cool perks: Access to Google offices, cafes, wellness centers, personal training sessions, massages, haircuts, bike repairs, office transportation, commuter benefits and so much more. To support your wellbeing at home, you can enjoy at-home fitness and cooking classes, and more.
* Please note that while our benefits philosophy is the same in every place Waymonauts work, benefits may vary by office/country and are subject to eligibility requirements.
Note: The following is only applicable for roles hired in the US. As we keep the safety of our employees and our communities top of mind, COVID-19 vaccinations continue to be a critical prevention measure to help end the pandemic. Because of this, Waymo requires all US-based employees who perform work onsite for Waymo to be fully vaccinated against COVID-19. If you are unable to be vaccinated, Waymo will provide a reasonable accommodation consistent with applicable law.