Location requirements
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 Perception team at Waymo builds technology that powers the Waymo Driver. Our models allow the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We conduct research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, allowing ML practitioners like you to develop multi-modal models and techniques at scale.
You will report to our Head of Perception.
You will:
Work closely with Perception engineers and build a deep understanding of the ML development workflows and systems, their requirements in order to achieve the desired development velocity, key systems constraints (latency, scale, budget, etc.). Such systems include: large-scale data extraction for model training, large model training pipelines, model inference systems, etc.
Work closely with all the infrastructure teams that Perception model systems are built upon, to ensure optimal sharing of infrastructure and optimal performance for scaling and achieving efficient and large-scale model development
Drive multi-year roadmaps on the Perception model systems, with the anticipated scale driven by business and technology roadmaps, as well as engineering efficiency
Work with both the infra teams and Perception model teams on system designs
Drive effective collaborations and execution among perception teams and infrastructure teams
You have:
15+ years of progressive experience in software engineering, with extensive experience in a technical leadership role.
Track record of designing and building large-scale systems supporting model development (data, training, inference), with very large-scale data, and very large worker payload
Track record in solving users’ needs end to end - working closely with the model engineers, and working backwards from the user / product needs to design and evolve the systems
Organizational awareness, extremely collaborative, strong communication, focus on value add to the company and to the team
We prefer:
Experienced at driving cross-org efforts in transitioning large systems through major evolutions while supporting high production demands
Experienced at modern ML data, training, and inference systems for large models
Experienced at budget management (compute, storage, memory, etc.) supporting workflows for O(hundred) model developers
Track record coaching and growing engineers and leaders
#LI-Hybrid
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.
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Waymo stands for a new way forward in mobility. We started as the Google self-driving car project in 2009 and we are now an independent self-driving technology company with a mission to make it safe and easy for people and things to move around.
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