Senior Staff Machine Learning Engineer, Agentic Systems at Moveworks

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.

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.

Aeva, Inc. is seeking a Machine Learning Engineer with a focus on Perception to join the team in Mountain View, CA. This role centers on developing algorithms that help autonomous systems interpret and respond to their environment. The work draws on both machine learning and computer vision to improve how autonomous vehicles perceive the world around them. Key responsibilities Design and build perception algorithms for autonomous platforms Use machine learning and computer vision on real-world datasets Support progress in autonomous vehicle technology through technical contributions Work closely with engineers and researchers to expand product capabilities Location This position is based in Mountain View, CA.

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, 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 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.

Waymo is at the forefront of autonomous driving technology, committed to becoming the world's most reliable 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 significantly reduce the number of lives lost to traffic accidents. The Waymo Driver underpins our fully autonomous ride-hailing service and can be adapted to various vehicle platforms and applications. With over ten million rider-only trips completed, our technology has autonomously navigated more than 100 million miles on public roads and billions in simulation across over 15 U.S. states.The Perception team is responsible for creating systems that learn the spatial-temporal representation and semantic meanings of the self-driving car's environment. Our work involves close collaboration with downstream teams for optimization and integration with the Waymo Driver. We engage in innovative research to tackle real-world challenges while partnering with Alphabet's research teams. With access to extensive driving data from diverse sensors, our engineers are equipped to (1) devise methods for continuous learning from vast real-world datasets, (2) develop scalable models and training processes, (3) analyze real-world behaviors to manage complex interactions, and (4) optimize models for both onboard and offboard hardware.Within the Perception domain, our Sensor Pipelines team addresses a variety of real-world challenges beyond mere object detection, including weather conditions, road surface understanding, visibility, and the identification of exceptional events surrounding the vehicle. These pipelines encompass a wide range of sensing technologies while integrating throughout the Perception stack and collaborating with planning components.In this hybrid role, you will report to a Director and lead a team of engineers dedicated to Perception machine learning pipelines.Your Responsibilities:Oversee large teams of software engineers tackling diverse Perception product challenges through machine learning, focusing on team development and recruitment to foster resilient, high-performing teams.Guide the team in designing top-tier machine learning solutions in partnership with Technical Leads, nurturing an environment of excellence and high achievement.Act as the team's representative within the broader Perception and Onboard group, collaborating with other leaders on staffing and strategic planning. Establish team Objectives and Key Results (OKRs) and formulate actionable plans to achieve them.

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.

Join Waymo as a Senior Staff Machine Learning Engineer specializing in Depot Automation, where you will play a vital role in transforming the future of transportation through cutting-edge machine learning solutions.Your expertise will drive innovation and efficiency, ensuring our autonomous vehicles operate seamlessly in various environments. Collaborate with a team of passionate engineers and researchers to develop and implement advanced algorithms that enhance our depot operations.

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.

Waymo is at the forefront of autonomous driving technology, committed to becoming the world's most trusted driver. Originating as the Google Self-Driving Car Project in 2009, our focus has been on developing the Waymo Driver—The World’s Most Experienced Driver™. Our mission is to enhance mobility access while significantly reducing traffic-related fatalities. The Waymo Driver powers our fully autonomous ride-hail service and is adaptable to various vehicle platforms and use cases. With over ten million rider-only trips facilitated, our technology has driven over 100 million miles on public roads and tens of billions in simulated environments across more than 15 U.S. states.The Perception team is responsible for designing systems that learn spatial-temporal representations and their semantic meanings within the self-driving car's environment. We collaborate with downstream teams for optimization and integration into the Waymo Driver. Our research addresses real-world challenges while working alongside Alphabet's research teams. By utilizing millions of miles of driving data from diverse sensors, engineers are empowered to (1) create efficient learning methods from large-scale real-world data, (2) develop scalable models and training processes, (3) analyze real-world behaviors to manage the complexities of real-world interactions, and (4) optimize models for both our onboard and offboard hardware.In this hybrid role, you will report directly to a Senior Staff Technical Lead Manager.

Coupang is hiring a Senior Staff II, Machine Learning Engineer (Tech Lead) for the Search team in Mountain View, USA. This position centers on building and enhancing the core technology behind search for one of South Korea’s largest e-commerce platforms. Role overview This role focuses on designing, developing, and refining machine learning systems that directly impact how millions of people shop online. As a technical lead, expect to work on projects that shape the search experience and improve the accuracy and speed of results for Coupang’s customers. Team and culture Coupang encourages teams to launch new initiatives and solve complex problems. Employees regularly see the results of their work, both in personal growth and in the company’s progress. The culture blends the drive of a startup with the stability and resources of a global public company. What makes this role unique Work on technology that influences how millions shop online. Join a team that prioritizes innovation and ongoing improvement. Contribute to a company known for transforming e-commerce in South Korea. Experience the energy of a startup with the support of a global organization. This is a chance to help define the future of commerce as part of Coupang’s technology-driven Search team.

Waymo, a leader in autonomous driving technology, aims to become the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo is dedicated to creating the Waymo Driver—The World's Most Experienced Driver™—to enhance mobility accessibility while significantly reducing traffic-related fatalities. Our technology powers a fully autonomous ride-hail service and is adaptable across various vehicle platforms and applications. The Waymo Driver has successfully completed over ten million rider-only trips, supported by extensive real-world driving data accumulated over 100 million miles on public roads and tens of billions in simulated environments across more than 15 U.S. states.The Perception team is instrumental in developing the system that interprets the spatial-temporal representation and semantic meanings of the car's surroundings. Our collaboration extends to downstream teams for optimization and integration into the Waymo Driver. Engaging in innovative research, we tackle real-world challenges and partner with research experts at Alphabet. With access to millions of miles of diverse sensor data, our engineers focus on developing scalable learning methods from large-scale real-world data, model training, behavioral analysis, and optimization for both onboard and offboard hardware.In this hybrid position, you will report directly to a Staff Technical Lead Manager.

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 developed the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and save thousands of lives currently lost to traffic accidents. The Waymo Driver operates Waymo’s fully autonomous ride-hail service and is adaptable to various vehicle platforms and use cases. With over ten million rider-only trips, our technology has autonomously driven more than 100 million miles on public roads and processed tens of billions of miles in simulation across more than 15 U.S. states.The Waymo ML Frameworks & Efficiency team collaborates closely with Research and Production teams to design and implement models in Perception and Planning, which are essential components of our autonomous driving software. We provide our partners with the most effective frameworks for the entire model development lifecycle and innovative efficiency solutions for model execution, tailored to the unique challenges of machine learning in autonomous driving.We are seeking talented engineers with expertise in ML frameworks or ML systems to enhance computational efficiency in both cloud environments and vehicle systems. You will engage with the entire ML stack, from deep learning model architectures to accelerator runtimes, working alongside ML modeling teams to drive large-scale efficient model training and inference.

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 company in autonomous driving technology, dedicated to becoming the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has been on a mission to develop the Waymo Driver—The World’s Most Experienced Driver™—which aims to enhance mobility access and prevent the thousands of fatalities caused by traffic accidents. The Waymo Driver is the backbone of our fully autonomous ride-hail service and is adaptable to various vehicle platforms and applications. With more than ten million rider-only trips completed, our technology has successfully navigated over 100 million miles on public roads and simulated tens of billions of miles across more than 15 U.S. states.The Perception team is responsible for creating the systems that learn the spatial-temporal representation and semantic meanings of the environment surrounding the autonomous driving vehicle (ADV). Our work involves close collaboration with downstream teams to optimize and integrate these systems into the Waymo Driver. We actively conduct research to solve real-world challenges and partner with research teams at Alphabet. With access to millions of driving data miles collected from a variety of sensors, our engineers have the opportunity to (1) devise methods for continuous learning from large-scale real-world data, (2) build and train models at scale, (3) analyze real-world behavior and develop systems to manage complex interactions with the environment, and (4) refine models for our onboard and offboard hardware.In this hybrid role, you will report to a Technical Lead Manager.

Waymo, a leader in autonomous driving technology, is dedicated to becoming the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has committed to developing the Waymo Driver—The World's Most Experienced Driver™—which not only enhances mobility access but also aims to save lives lost in traffic accidents. The Waymo Driver powers our fully autonomous ride-hailing service and is adaptable across various vehicle platforms and applications. With over ten million rider-only trips completed and more than 100 million miles driven autonomously on public roads, plus extensive simulation across 15+ U.S. states, Waymo is setting the standard for safety and innovation in transportation.In this hybrid role, you will report to the Sr. Staff Manager.

Waymo is at the forefront of autonomous driving technology, dedicated to becoming the most trusted driver in the world. Originating from the Google Self-Driving Car Project in 2009, Waymo has made significant strides in developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility and save lives lost in traffic accidents. Our technology powers a fully autonomous ride-hailing service and is adaptable across various vehicle platforms and applications. With over ten million rider-only trips and 100 million miles driven autonomously on public roads, our experience is unmatched.As part of the DUE ML Core team, you will play a pivotal role in building and managing scalable machine learning and data systems, refining simulation workflows, and enhancing developer onboarding experiences. This position combines expert human insight with cutting-edge machine learning models to produce training and evaluation data for a multitude of metrics and components integral to the Waymo Driver. We seek passionate researchers and software engineers eager to advance machine learning methodologies for our autonomous vehicle evaluation systems and continuously improve the performance of our technological framework.