Machine Learning Engineer - Perception

Waymo, an innovator in autonomous driving technology, is dedicated to becoming the world's most reliable driver. Originating as the Google Self-Driving Car Project in 2009, our focus has been on creating the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and prevent traffic-related fatalities. The Waymo Driver supports our fully autonomous ride-hail service and can be integrated into various vehicle platforms for diverse applications. With over ten million rides provided and experience from driving more than 100 million miles on public roads combined with billions of miles in simulation across 15+ U.S. states, we’re at the forefront of a transportation revolution.The Perception team is responsible for developing systems that learn spatial-temporal representations and their semantic meanings within the autonomous vehicle's environment. Collaborating closely with other teams for optimization and integration into the Waymo Driver, we engage in research to tackle practical challenges and work with Alphabet's research teams. With access to millions of miles of diverse driving data, our engineers can (1) create methods for efficient and continuous learning from large-scale real-world data, (2) build and train models at scale, (3) analyze real-world behavior to manage complex interactions, and (4) optimize models for our onboard and offboard hardware.In this hybrid role, you will report directly to a Technical Lead Manager.

Waymo, an innovative leader in autonomous driving technology, is on a mission to redefine mobility by creating the world's most trusted driver. Originating as the Google Self-Driving Car Project in 2009, Waymo has been dedicated to developing the Waymo Driver—The World's Most Experienced Driver™—aimed at enhancing mobility access and preventing traffic-related fatalities. Our autonomous ride-hail service, powered by the Waymo Driver, has completed over ten million trips, with an impressive track record of driving more than 100 million miles on public roads and tens of billions in simulations across 15+ U.S. states.The Perception team plays a crucial role in this journey by constructing systems that learn and interpret the spatial-temporal representations and semantic meanings of the environments surrounding our self-driving vehicles. We collaborate closely with other teams to optimize and integrate these systems into the Waymo Driver, while also conducting cutting-edge research to tackle real-world challenges. Our engineers leverage vast datasets from diverse sensors, allowing them to (1) devise methods for continuously learning from large-scale real-world data, (2) create scalable models and training processes, (3) analyze real-world behaviors to navigate complex interactions, and (4) optimize models for both onboard and offboard hardware.In this hybrid role, you will report to a Technical Lead Manager within the Semantics subgroup of our Perception organization.

Waymo is at the forefront of autonomous driving technology, dedicated to becoming the world’s most trusted driver. Originating as the Google Self-Driving Car Project in 2009, Waymo has tirelessly developed the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and save lives lost to traffic accidents. The Waymo Driver powers our fully autonomous ride-hailing service, and its technology can be adapted to a variety of vehicle platforms and applications. With over ten million rider-only trips and extensive experience driving over 100 million miles on public roads, alongside tens of billions of miles in simulation across more than 15 U.S. states, our capabilities are unparalleled.The Perception team is integral to Waymo, developing the advanced technology that enables the Waymo Driver to accurately perceive its surroundings, make timely decisions, and ensure safe transportation for passengers. We are engaged in cutting-edge research that addresses tangible challenges and fosters collaboration with research teams at Alphabet. With access to vast amounts of driving data from diverse sensors, we empower machine learning practitioners to create multi-modal models and techniques on a grand scale.In this hybrid role, you will report directly to the Director of Engineering.

About the RoleJoin our dynamic team of experts where machine learning and systems engineering intersect to enhance the performance of autonomous systems. As a Senior Software Engineer specializing in Perception Machine Learning Data, you will play a crucial role in integrating machine learning advancements with autonomy infrastructure, ensuring that our models are trained using the most pertinent, diverse, and high-quality datasets. Your contributions will significantly influence how autonomous systems recognize uncommon scenarios, adapt to various geographical contexts, and operate safely at scale.Key Responsibilities Include:Utilizing Vision Language Models (VLMs) to compile diverse datasets that reflect real-world driving patterns across different regions.Creating high-fidelity synthetic data frameworks across multiple sensor modalities.Enhancing machine learning-powered validation processes for data quality and model preparedness.Your Impact:High-Output Generalist: Collaborate across various domains including autonomy, infrastructure, databases, simulation, and machine learning development, while expanding your expertise in Robotics and ML.Robotics Specialist: Develop cutting-edge solutions for data discovery, automated labeling, and synthetic data generation in close cooperation with the Infrastructure and Autonomy teams.About the WorkTackle the most demanding data challenges in autonomy by applying machine learning and rigorous systems engineering principles:Design hybrid systems that combine deep learning with traditional algorithms for scalable data curation and annotation.Create frameworks to evaluate the real-world authenticity of synthetic data and enhance the quality of synthetic data rendering.Develop tools to automatically identify data gaps that affect the performance of perception models.Collaborate with autonomy engineers to transform raw sensor data into prioritized training objectives, addressing critical gaps that hinder perception and autonomy performance.About YouBachelor’s degree in Computer Science, Robotics, Statistics, Physics, Mathematics, or a related quantitative field.Experience:4+ years of professional software engineering experience, proficient in Python and familiar with C/C++. Demonstrated ability to lead cross-functional technical projects from conception to execution.You have hands-on experience in implementing machine learning solutions and enjoy embedding them into practical systems. Your focus is on delivering impactful, integrated solutions rather than solely theoretical ML projects.Bonus PointsExperience working with synthetic or autonomous driving data.Background in building machine learning systems for robotic applications.

Waymo is at the forefront of autonomous driving technology, dedicated to becoming the world's most trusted driver. Established in 2009 as the Google Self-Driving Car Project, Waymo has developed the Waymo Driver—The World’s Most Experienced Driver™—aimed at enhancing mobility access and saving countless lives from traffic-related accidents. Our technology empowers a fully autonomous ride-hail service and is adaptable across various vehicle platforms and product applications. With over ten million rider-only trips facilitated by the Waymo Driver and more than 100 million miles driven autonomously on public roads, we are paving the way for safer transportation.The Perception team is responsible for developing systems that interpret the spatial-temporal representations and semantic meanings of the environment surrounding our autonomous vehicles. Our collaborative efforts with downstream teams focus on optimizing and integrating these systems within the Waymo Driver. We engage in innovative research to tackle real-world challenges and work closely with research teams at Alphabet. Our engineers have access to extensive driving data from diverse sensors, allowing us to (1) create efficient learning methods from vast real-world datasets, (2) build and train models at scale, (3) analyze real-world behaviors, and (4) optimize models for both onboard and offboard hardware.In this hybrid role, you will report to a Technical Lead Manager.

Waymo is at the forefront of autonomous driving technology, striving to become the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo is dedicated to advancing the Waymo Driver—The World's Most Experienced Driver™—to enhance mobility and save lives that are often lost to traffic accidents. The Waymo Driver not only powers our fully autonomous ride-hail service but is also adaptable across various vehicle platforms and use cases. With over ten million rider-only trips completed, our technology has driven autonomously for more than 100 million miles on public roads, supported by tens of billions of miles in simulation across 15+ U.S. states.Our Compute Team plays a pivotal role in delivering the compute platform that runs the software stack of fully autonomous vehicles. We specialize in designing high-performance custom silicon, developing cutting-edge system-level compute architectures that maximize performance, power efficiency, and minimize latency. Our multidisciplinary team thrives on collaboration, working closely with various engineering teams to ensure both hardware and software are optimized for peak performance. We are looking for passionate and talented individuals to join us in developing one of the highest-performing automotive compute platforms in the world.In this hybrid role, you will report to a Hardware Engineering Manager.

Waymo is at the forefront of autonomous driving technology, aiming to become the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has dedicated itself to developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and reduce the tragic loss of life due to traffic accidents. The Waymo Driver powers our fully autonomous ride-hailing service and can be adapted to various vehicle platforms and use cases. With over ten million rider-only trips and extensive experience driving autonomously over 100 million miles on public roadways, complemented by tens of billions of miles in simulations across 15+ U.S. states, we are leading the way in this transformative field.The Perception team is responsible for creating the systems that learn the spatial-temporal representations and semantic meanings of the self-driving car's surroundings, effectively enabling the car to 'perceive' its environment. We collaborate closely with downstream teams to optimize and integrate our findings into the Waymo Driver. Our research tackles real-world challenges, leveraging vast amounts of driving data from diverse sensors. As part of our team, you will work on methods for continuous learning from large-scale real-world data, model development and training at scale, behavioral analysis, and system optimization for both onboard and offboard hardware.In this hybrid role, you will report to a Senior Staff Technical Lead Manager.

Waymo is a pioneering autonomous driving technology firm on a mission to become the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has been dedicated to developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access while aiming to save thousands of lives lost in traffic accidents. The Waymo Driver serves as the backbone for our fully autonomous ride-hail service and has the potential to be integrated across various vehicle platforms and applications. With over ten million rider-only trips facilitated by its extensive experience of more than 100 million miles driven autonomously on public roads and tens of billions of miles in simulation across over 15 U.S. states, Waymo is at the forefront of autonomous technology.At Waymo, machine learning models form the essence of our fully autonomous driving capabilities. These models empower the Waymo Driver to interpret its surroundings, make accurate decisions, and transport individuals safely to their destinations. We tackle intricate technical challenges in perception, planning, and control, collaborating closely with hardware and systems engineers. If you are passionate about Level 4 autonomous driving, we would love to connect with you.As an intern at Waymo, you will collaborate with industry leaders on impactful projects that contribute significantly to our mission. We believe in a reciprocal learning experience: you will apply your expertise while gaining opportunities to expand your skill set. Interns are integral to our culture and serve as a vital part of our talent pipeline. Join Waymo for an engaging and fulfilling internship experience!This internship will be conducted on-site at our headquarters in Mountain View, CA.

Waymo is a pioneering autonomous driving technology company with a vision to become the most trusted driver in the world. Originating from the Google Self-Driving Car Project in 2009, we have dedicated ourselves to developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access while preventing countless lives lost in traffic accidents. The Waymo Driver is the backbone of our fully autonomous ride-hailing service and can be adapted to various vehicle platforms and product use cases. To date, the Waymo Driver has successfully completed over ten million rider-only trips, backed by its extensive experience of autonomously navigating over 100 million miles on public roads and tens of billions of miles in simulation across more than 15 U.S. states.The Perception team is responsible for creating the systems that interpret spatial-temporal representations and their semantic meanings of the environment surrounding the self-driving car. We collaborate closely with downstream teams to optimize and integrate these systems into the Waymo Driver. Our team conducts innovative research to solve real-world challenges and partners with research teams at Alphabet, leveraging millions of miles of driving data from a diverse range of sensors. This enables our engineers to (1) devise methods for continuous learning from large-scale real-world data, (2) design and scale model training, (3) analyze real-world behavior and develop systems for managing real-world complexities, and (4) optimize models for our onboard and offboard hardware.In this hybrid role, you will report to a Senior Staff Technical Lead Manager.

Who We Are Nuro is at the forefront of self-driving technology, dedicated to making autonomous driving accessible to everyone. Established in 2016, we are engineering the world’s most scalable driving solution by merging advanced AI with automotive-grade hardware. Our proprietary technology, the Nuro Driver™, is licensed to support a variety of applications, from robotaxis and commercial fleets to personal vehicles. With years of successful self-driving deployments, Nuro provides automakers and mobility platforms a clear pathway to achieving commercial-scale autonomous vehicles, fostering a safer, more connected future. About the Work Design and enhance state-of-the-art generative models, particularly focusing on diffusion architectures, flow-matching techniques, and energy-based models for autonomous planning. Develop generative models utilizing foundation models. Harness large language models and world foundation models for reasoning, decision-making, and multi-modal generation. Optimize generative models through reinforcement learning to enhance interactive reasoning. Investigate reward modeling and learned verifiers using generative models. Explore joint prediction and planning as well as self-play, and leverage generative models for active learning and world modeling. Create controllable generative models to direct the generation process towards specific goals, conditions, and rewards. Collaborate with autonomy teams to propose and implement holistic solutions to pressing autonomy challenges. Assess issues, suggest solutions, prioritize tasks, and evaluate your findings by deploying models on the Nuro Driver.

Waymo is at the forefront of autonomous driving technology, dedicated to becoming the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has tirelessly worked on developing the Waymo Driver—The World's Most Experienced Driver™—to enhance mobility access and save lives lost to traffic accidents. The Waymo Driver fuels our fully autonomous ride-hailing service and can adapt to various vehicle platforms and applications. With over ten million rider-only trips completed, Waymo has amassed more than 100 million miles driven autonomously on public roads, supplemented by tens of billions of simulated miles across 15+ U.S. states.The Perception team at Waymo is instrumental in crafting the technology that empowers the Waymo Driver. Our advanced models enable the Waymo Driver to interpret its surroundings, make informed decisions, and ensure safe passage for passengers. Engaging in research to tackle real-world challenges, we collaborate closely with Alphabet's research teams. Our access to extensive driving data from diverse sensors allows machine learning practitioners to develop scalable multi-modal models and techniques.You will report directly to our Director of Engineering within the Perception Organization.

Company OverviewAt Matic Robotics, we are dedicated to transforming the way people manage household chores, reclaiming the 2.5 trillion hours spent on such tasks every year through innovative home robotics.Our flagship product, the Matic cleaning robot, employs advanced spatial AI technology, including real-time 3D mapping and adaptive path tracking, allowing it to autonomously navigate and clean homes with precision. Designed to function with just RGB cameras and on-device neural networks, Matic is built for real-world efficiency.Privacy is paramount at Matic. Our robots operate with a 'privacy-first' approach, processing all data on-device instead of relying on the cloud.We believe in a progressive evolution of home robotics, starting with specialized robots that gradually evolve into more complex systems.Matic fosters a collaborative and dynamic work culture, where our passionate team is committed to creating cherished products that save time and enhance everyday living.About the RoleWe are seeking a driven and innovative Perception Engineer to join our team and make a significant impact from the outset.Key ResponsibilitiesTranslate complex real-world challenges into well-defined machine learning tasks.Develop and implement cutting-edge computer vision algorithms.Create novel neural network architectures tailored for robotic applications.Design and execute robust 3D geometry-based vision algorithms.Establish scalable machine learning infrastructures for large datasets, ensuring reproducibility.Analyze outputs and continuously optimize algorithm accuracy and efficiency.Deploy machine learning models on edge devices without compromising performance.Contribute to achieving Level 5 autonomy in consumer robotics.Collaborate across interdisciplinary teams, including Hardware, Electrical, and Systems Engineers.

Waymo is a pioneering force in autonomous driving technology, dedicated to becoming the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo's mission focuses on creating the Waymo Driver—The World’s Most Experienced Driver™—with the goal of enhancing mobility access and significantly reducing traffic-related fatalities. The Waymo Driver is the backbone of our fully autonomous ride-hailing service and is adaptable across various vehicle platforms and applications. With over ten million rider-only trips completed and the experience of driving autonomously for over 100 million miles on public roads, alongside tens of billions of miles in simulation across more than 15 U.S. states, we are committed to transforming the future of transportation.The Simulator Team at Waymo is at the forefront of innovation, developing advanced simulations that replicate realistic environments for the testing, training, and validation of the Waymo Driver. Our team comprises a diverse, collaborative group of machine learning (ML) engineers, software engineers, and ML research engineers, who are dedicated to crafting industry-leading simulation solutions. Utilizing cutting-edge generative and reconstructive ML algorithms, we model the real world, including realistic agents, road systems, traffic dynamics, weather conditions, and a comprehensive sensor suite (Camera, Lidar, Radar).In this exciting role, you will be instrumental in enhancing the fidelity, scalability, controllability, and richness of our simulations by exploring the latest advancements in 3D world modeling. By leveraging state-of-the-art ML technologies trained on extensive datasets, you will help us create dynamic, semantically rich virtual worlds that have a direct impact on the development and validation of the Waymo Driver.You will report directly to a Senior Staff Engineering Manager.Responsibilities:Lead the design, development, and deployment of innovative 4D world models and generative systems aimed at generating ultra-realistic and controllable sensor outputs and semantics for simulation applications at Waymo.Architect and implement scalable, robust ML pipelines for the training, evaluation, and deployment of large-scale generative models within our simulation framework, employing techniques like model distillation and quantization.Develop and scale production-ready video generation methodologies (e.g., Diffusion, Flow Matching) to create dynamic and interactive simulation environments.Utilize Vision Language Models (VLMs) to enhance semantic comprehension and control within our world simulation products.Collaborate with leading research teams across Waymo and Alphabet to integrate state-of-the-art research in 4D world modeling and generative AI into scalable, production-ready solutions.Provide mentorship and technical guidance to fellow engineers on the team.

Waymo is pioneering the future of autonomous driving technology with a vision to become the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has dedicated itself to creating the Waymo Driver—The World’s Most Experienced Driver™—which aims to enhance mobility access and save countless lives lost in traffic accidents. Powering Waymo’s fully autonomous ride-hailing platform, the Waymo Driver is adaptable across various vehicle types and applications. With over ten million rider-only trips achieved and a remarkable track record of driving more than 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states, Waymo is at the forefront of transforming transportation.The Driver Understanding and Evaluation team at Waymo is crucial in developing an in-depth understanding of the Waymo Driver's behavior. With an impressive capacity of over one million driverless miles each week, it is essential for Waymo to comprehend and evaluate all vehicle behaviors—both in real-world scenarios and simulations—through automated algorithms. The learned metrics team is a strategic initiative employing machine learning to scale and meet Waymo's ambitious goals. We work collaboratively across various teams to transition machine learning into production systems and establish Waymo’s reward function. Our focus is on building and maintaining large-scale machine learning and data systems, simulation workflows, and analytical tools. By merging expert human insights with cutting-edge machine learning models, we provide training and evaluation data for the Waymo driver. We seek enthusiastic researchers and software engineers who are passionate about creating robust production-grade machine learning systems for our autonomous vehicles and possess an unwavering commitment to enhancing our technology stack's performance.

Waymo seeks a Senior Machine Learning Engineer with a focus on Large Language Model (LLM) and Vision-Language Model (VLM) distillation. This role is based in Mountain View, California, and centers on advancing the machine learning models that drive Waymo’s autonomous vehicles. Collaboration with both data science and engineering teams is a key part of the work, with an emphasis on refining and optimizing model performance. Key responsibilities Design and implement algorithms to distill LLMs and VLMs for greater efficiency. Work with large datasets to support learning and adaptation in self-driving systems. Partner with cross-functional teams to bring optimized models into production environments. Continually improve the performance and efficiency of models that power autonomous driving technology. Requirements Hands-on experience with machine learning, with a strong background in LLM and VLM distillation. Proven problem-solving skills and the ability to apply machine learning creatively to practical challenges. Interest in tackling real-world problems related to autonomous vehicles.

About UsNuro is pioneering self-driving technology with a mission to make autonomy accessible for everyone. Established in 2016, we are developing the world's most scalable driver, integrating advanced AI with automotive-grade hardware. Our flagship technology, the Nuro Driver™, is licensed to facilitate diverse applications, ranging from robotaxis to commercial fleets and personal vehicles. With years of proven deployment in self-driving environments, Nuro offers automakers and mobility platforms a viable pathway to commercial-scale autonomous vehicles, creating a safer, more connected future.Role OverviewAs a Senior/Staff Machine Learning Research Scientist, you will work closely with multidisciplinary teams, focusing on generative modeling to solve complex planning challenges in autonomous driving. You will utilize cutting-edge techniques—including diffusion models, flow matching, and energy-based models—to create innovative solutions that enable safe and efficient driving behavior in real-world scenarios. Additionally, you will manage the complete lifecycle of your models, transitioning them into robust applications for global autonomous driving deployments.Key ResponsibilitiesDesign and enhance state-of-the-art generative models, particularly focusing on diffusion architectures, flow-matching methods, and energy-based models, aimed at autonomous plan generation.Integrate large language models and world foundation models to facilitate reasoning, decision-making, and multi-modal generation.Employ reinforcement learning to optimize generative models for interactive reasoning, and investigate reward modeling and self-play methodologies.Create controllable generative models that steer the generation process towards specific goals and conditions.Collaborate with various autonomy teams to develop comprehensive solutions for key challenges in autonomous technology, ensuring rigorous evaluation through deployment on the Nuro Driver.

Waymo is a leader in autonomous driving technology dedicated to becoming the most trusted driver in the world. Originating from the Google Self-Driving Car Project in 2009, our focus has been on creating the Waymo Driver—an exceptional driver that enhances mobility access while significantly reducing traffic-related fatalities. The Waymo Driver not only supports our fully autonomous ride-hailing service but can also be adapted to various vehicle platforms and applications. With over ten million rider-only trips completed, our technology has safely navigated more than 100 million miles on public roads and processed tens of billions of miles in simulation across over 15 U.S. states.The Perception Data team at Waymo plays a critical role in shaping the strategy and technical direction for all data utilized in training and evaluating the Waymo Driver's perception capabilities. We manage the complete data lifecycle, developing automated systems and 'infrastructure-as-product' solutions that convert vast amounts of driving sensor data into high-quality training datasets. Our team tackles complex challenges, including active learning loops and open-vocabulary modeling, bridging raw data with advanced machine learning techniques.By integrating data ingestion, curation, and evaluation into a unified ecosystem, we facilitate the swift development of foundational models and next-generation perception systems. We work closely with Machine Learning, Infrastructure, and Evaluation teams to address intricate data challenges, ensuring our models can effectively interpret the long-tail of rare events. Ultimately, our contributions lay the groundwork for the Waymo Driver to operate safely in diverse environments.

What You'll Be DoingJoin Moveworks as a Senior Machine Learning Engineer focused on developing advanced ML infrastructure for deploying and managing Large Language Models (LLMs). This pivotal role involves the design, optimization, and scaling of comprehensive machine learning systems that drive our AI solutions. The ML Infrastructure team is responsible for a range of critical functions, including distributed training and inference pipelines, model evaluation, and latency optimization for LLMs. Our work supports numerous ML and NLP models currently in production, impacting millions of enterprise users. You will tackle real-world challenges related to service scalability and algorithm optimization.Your collaboration with our machine learning team, data infrastructure team, and various cross-functional experts will directly enhance our customers' AI experience. This is an opportunity to play a vital role in the long-term scalability of our core AI product and the success of the company. If you seek a high-impact, fast-paced environment to elevate your career, we want to hear from you!Design, develop, and enhance scalable machine learning infrastructure for training, evaluating, and deploying LLMs.Create abstractions to automate diverse steps in various ML workflows.Collaborate with interdisciplinary teams of engineers, data analysts, machine learning specialists, and product managers to introduce innovative features.Utilize your expertise to promote best practices in machine learning and data engineering.

Waymo is looking for a Senior Machine Learning Engineer focused on Runtime and Serving to help advance autonomous vehicle technology in Mountain View, CA. Role overview This position centers on developing and improving machine learning systems that support safe and efficient vehicle operation. The work involves optimizing algorithms and increasing the performance of deployed models in real-world conditions. What you will do Lead the design and implementation of machine learning systems used in autonomous vehicles Work on runtime and serving infrastructure to ensure reliable and efficient model deployment Contribute expertise to optimize algorithms for safety and operational performance Impact Your contributions will directly affect how Waymo's vehicles interpret and respond to their environment, supporting safer and more reliable autonomous driving.