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The ML Platform team at Waymo provides a set of tools to support and automate the lifecycle of the machine learning workflow, including feature and experiment management, model development, optimization and monitoring. These efforts have resulted in making machine learning more a
The Waymo ML Infrastructure team accelerates Waymo’s mission, by building the best ecosystem for sustainably innovating and shipping ML powered intelligence. Research, Production, and the Hardware teams are our primary stakeholders and our work powers the development of the stat
The Simulator team builds state-of-the-art simulations of realistic environments for the testing and training of the Waymo driver. We use machine learning to model the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists etc.), roads, traffic con
- Report into the TLM for the Learned Metrics Team - Develop ML models that assess our autonomous vehicle's behavior. - Develop ML infrastructure to support performant models. - Collaborate across teams to bring state-of-the-art to production. - BS in Computer Science, Roboti
As an L4 Policy & Quality Specialist, you will serve as the Mountain View operational backbone of the Labeling Policy Program. You will play a key role in accelerating MTV Perception Engineering velocity by translating complex machine learning data requirements into consistent, h
This role follows a hybrid work schedule and you will report to the Senior Staff Silicon Engineer. - Work with researchers and architects to translate high level requirements into hardware features - Specify and design microarchitectures to deliver world class ML performance -
The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate an
In this hybrid role, you will report to an Engineering Manager - Report into the TLM for the Learned Metrics Team - Develop ML models that assess our autonomous vehicle's behavior. - Develop ML infrastructure to support performant models. - Collaborate across teams to bring s
The DUE Machine Learning team will build and operate scalable machine learning and data systems, simulation workflow and insight tools, improve and speed up the evaluation and onboard developer journeys. It will combine expert human judgements and advanced machine learning models
TaaS (Transportation as a Service) is responsible for building an amazing user experience and business around the Waymo Driver. We are responsible collectively for Growth, Territory Expansion, Service Quality (including pickup, dropoff and routing), Marketplace (pricing, position
The Simulator team builds state-of-the-art simulations of realistic environments for the testing and training of the Waymo driver. We use machine learning to model the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists etc.), roads, traffic con
The Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the autonomously driving vehicle (ADV), i.e., the system that “perceives” the world around the car. We work jointly with downstream
Waymo's core business scale is bottlenecked by improving long tail behaviors. The growth in vehicles, platforms, geos (e.g. international), and ODD (e.g. weather) creates a huge set of new problems that we have to solve quickly. The methodical process of building driving sets and
This role follows a hybrid work schedule, and you will report to the Tech Lead Manager of the Machine Learning Performance team. - Build infrastructure and tooling to monitor and diagnose ML model compatibility and performance issues during other ML software development - Partn
As a Perception Machine Learning Engineer, you will build the intelligent systems that "see" the world, directly shaping the future of autonomous travel. Within the Perception team, we are tackling some of the most complex, open-ended challenges in autonomous driving. Our models
The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate an
The Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the autonomously driving vehicle (ADV), i.e., the system that “perceives” the world around the car. We work jointly with downstream
The Marketplace team builds the core decision systems that keep Waymo running smoothly. They design the algorithms that match riders to vehicles, optimize routing, balance supply and demand, forecast rider demand, and power dynamic pricing. Their work ensures the fleet stays effi
The Simulation ML Infrastructure team builds scalable AI/ML infrastructure to accelerate the Simulator team in sustainably innovating and building state of the art simulations of realistic environments for the testing and training of the Waymo Driver. To increase the fidelity and
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 com