ML Performance Engineer
Company: Waymo
Location: Mountain View
Posted on: May 8, 2024
Job Description:
ML Performance Engineer Mountain View, California, United States
New York, New York, United States 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. Software Engineering builds the brains of Waymo's fully
autonomous driving technology. Our software allows the Waymo Driver
to perceive the world around it, make the right decision for every
situation, and deliver people safely to their destinations. We
think deeply and solve complex technical challenges in areas like
robotics, perception, decision-making and deep learning, while
collaborating with hardware and systems engineers. If you're a
software engineer or researcher who's curious and passionate about
Level 4 autonomous driving, we'd like to meet you. 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:
- Collect application/ML model performance traces and analyze for
performance optimization opportunities
- Land the optimizations to the application/ML model code base
byEvaluating the correctness of the change (including retrain the
ML model to evaluate accuracy)
- Ensure the change is net-positive for the current onboard
performance
- Work with the application teams to adopt or apply the
optimizations
- Add proper testing to ensure optimized performance is tracked
and not regressed in the future
- Land the optimizations to the infrastructure byPrototype the
performance optimizations and evaluate its effectiveness on
applications/ML models
- Generalize the optimization at the infra level (compiler,
firmware, runtime, framework, etc.) and project the potential
impact to all applications (ML models) across board
- Motivate the infra teams to land the optimization to the
specific level of the stack, set the performance expectation
through solid methodology (e.g. roofline) and ensure the
infrastructure team is aligned about the expectation
- Once the optimization is landed by the infra teams, close the
loop by evaluating the overall performance impact and ensure it's
landed in the expected way At a minimum we'd like you to have:
- BS degree in Computer Science/Electrical Engineering or
equivalent, or equivalent practical experience
- 3+ years of experience writing complex C++ code
- 3+ years of experience writing code in Python
- 1+ years experience in optimizing compute performance for ML
applications
- Experience in compute architectures and performance analysis
optimization methodologies It's preferred if you have:
- Experience in ML compiler design and implementation
- Experience in performance tools, simulators, HW/SW
codesign
- Experience in robotic application
development/optimizations
- Proficiency in collaboration with application teams and
infrastructure teams 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), and special wellness
programs. Financial wellness: Your financial peace of mind is
important to us. At Waymo, we offer a great compensation package,
bonus opportunities, equity, a generous 401(k) plan, 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 or hybrid work model and offer remote working
opportunities, paid time off, 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 with up to 4 weeks of additional leave before
their due date, and non-birthing parent gets 18 weeks of paid
leave), and 20 days of subsidized 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 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, massages, and so much more. To support your wellbeing at
home, you can enjoy at-home fitness and cooking classes, and more.
#LI-Onsite 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 $192,000-$243,000 USD We
appreciate your interest in Waymo. Waymo is an equal employment
opportunity employer, committed to maintaining a supportive and
inclusive workplace for all employees. Waymo does not discriminate
against, and prohibits harassment of, any applicant or employee
based on race, color, sex, sexual orientation, gender identity,
religion, national origin, age, disability, military status,
genetic information or any other basis protected by applicable law.
Waymo will also consider for employment qualified applicants with
criminal records in accordance with applicable law. Waymo is
committed to ensuring equal opportunity for qualified individuals
with disabilities. If you are an individual with a disability and
require an accommodation to participate in the application or
interview process, please let the recruiting team know or email
waymo-candidatesupport@google.com. (This email address is intended
to be used only for requesting accommodations as part of the
application process. Other inquiries will not receive a
response.)
Keywords: Waymo, Newark , ML Performance Engineer, Engineering , Mountain View, California
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