Senior Machine Learning Research Scientist - Autonomous Driving

About Nuro Nuro is at the forefront of self-driving technology, dedicated to making autonomy accessible to everyone. Established in 2016, we are developing the world’s most scalable autonomous driver, integrating state-of-the-art AI with high-quality automotive hardware. Our proprietary technology, the Nuro Driver™, is licensed for a diverse array of applica…

About UsNuro is a pioneering self-driving technology firm committed to making autonomy accessible to everyone. Established in 2016, we are developing the world's most scalable autonomous driver by integrating advanced artificial intelligence with automotive-grade hardware. Nuro licenses its proprietary technology, the Nuro Driver™, for diverse applications including robotaxis, commercial fleets, and personal vehicles. With years of proven technology through self-driving deployments, we provide automakers and mobility platforms with a clear pathway to commercial-scale autonomous vehicles, fostering a safer, more interconnected future.Role OverviewAs a Staff ML Research Scientist, you will collaborate with our autonomy teams to tackle perception, prediction, and planning challenges using innovative machine learning techniques. Your expertise in foundation models, multi-modal LLMs, generative models, out-of-distribution detection, imitation learning, and reinforcement learning will be invaluable. If you are passionate about solving complex problems and eager to see your solutions implemented in real-world scenarios, we invite you to join our team!Key ResponsibilitiesConduct research and apply cutting-edge machine learning methodsAddress state-of-the-art challenges in perception, prediction, and planningDevelop and optimize efficient ML data pipelinesLead and mentor a diverse team of professionalsProduce and deploy autonomous software for public deployment

About Us Nuro is a pioneering self-driving technology company striving to make autonomous vehicles accessible for everyone. Since our founding in 2016, we have been dedicated to creating the world’s most scalable driver, integrating advanced artificial intelligence with automotive-grade hardware. Our flagship technology, the Nuro Driver™, is licensed to support various applications, including robotaxis, commercial fleets, and personally owned vehicles. With a track record of successful self-driving deployments, Nuro is paving the way for automakers and mobility platforms to realize the commercial potential of autonomous vehicles, fostering a safer, more connected future. Role Overview As a Senior Machine Learning Research Scientist focusing on Vision-Language-Action (VLA) models, you will enhance our onboard Behavior & Planning stack to promote safe and robust decision-making in complex driving scenarios. Your expertise will drive the development of multimodal models that integrate scene understanding, contextual reasoning, and planning-relevant representations for real-world autonomous driving. This position emphasizes advancing cutting-edge VLA models, including model development, large-scale training, fine-tuning, evaluation, and optimization for onboard deployment. You will collaborate closely with teams across behavior, planning, perception, systems, and infrastructure to translate research breakthroughs into practical applications deployed in our vehicles. If you are passionate about creating and implementing state-of-the-art VLA systems in robotics, we encourage you to apply. Key Responsibilities Develop and enhance VLA models for onboard Behavior & Planning in autonomous driving systems. Create multimodal models that facilitate safe decision-making in complex and ambiguous driving situations. Research and implement state-of-the-art techniques in vision-language-action modeling, multimodal representation learning, and foundational models for autonomy. Train, fine-tune, and evaluate large-scale VLAs utilizing diverse and real-world driving datasets to improve model quality and robustness. Optimize models for efficient onboard deployment, focusing on inference speed, memory usage, and runtime performance. Collaborate with various teams to define training, evaluation, and deployment requirements. Design effective evaluation methodologies for multimodal models in safety-critical scenarios. Contribute to scalable model and data pipelines that support rapid experimentation and deployment. Qualifications Proven expertise in machine learning, particularly in vision-language-action frameworks. Experience with multimodal model development and evaluation. Strong background in autonomous driving systems and decision-making processes. Familiarity with large-scale data training and optimization techniques. Excellent collaboration skills to work effectively with cross-functional teams.

About NuroNuro is pioneering self-driving technology with a vision to make autonomy universally accessible. Established in 2016, we are committed to developing the most scalable driving solution, integrating advanced AI with automotive-grade hardware. Our flagship technology, the Nuro Driver™, is licensed to facilitate various applications, including robotaxis, commercial fleets, and personal vehicles. With proven technology from numerous self-driving deployments, Nuro provides automakers and mobility platforms a clear pathway to achieving commercial-scale autonomous vehicles, fostering a safer, more connected future.Role OverviewAs a Lead Machine Learning Research Scientist, you will collaborate with our autonomy teams to address complex perception, prediction, and planning challenges using innovative machine learning techniques. This includes working with foundation models, multi-modal large language models, generative models, out-of-distribution detection, imitation learning, and reinforcement learning. If you thrive on tackling challenging problems and translating solutions into real-world applications, we invite you to join our team!Key ResponsibilitiesResearch and implement cutting-edge machine learning techniques.Address state-of-the-art perception, prediction, and planning issues within our autonomy system.Develop and optimize efficient ML data pipelines.Provide technical leadership and mentorship to a diverse team.Deploy autonomous software solutions on public roads.

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, our mission centers on the Waymo Driver—The World’s Most Experienced Driver™—aimed at enhancing mobility access while significantly reducing traffic-related fatalities. The Waymo Driver currently underpins our fully autonomous ride-hailing service and is versatile enough to be integrated into 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 executed tens of billions of miles in simulation across over 15 states in the U.S.The Waymo AI Foundations team is committed to advancing machine learning solutions that address the challenges of autonomous driving, enabling the safe operation of Waymo vehicles in numerous cities and under diverse driving conditions. We actively pursue collaborations with other research teams within Alphabet. Our current focus areas encompass reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.In this hybrid role, you will report directly to a Principal Scientist.

Who We AreNuro is at the forefront of self-driving technology, dedicated to making autonomy accessible for everyone. Founded in 2016, we are developing the most scalable autonomous driving system, merging advanced AI with automotive-grade hardware. Our flagship technology, the Nuro Driver™, is licensed for various applications, including robotaxis, commercial fleets, and personal vehicles. With years of successful deployments, Nuro provides automakers and mobility platforms a clear pathway to commercial-scale autonomous vehicles, paving the way for a safer and more connected future.About the RoleThe Prediction team is tasked with leveraging cutting-edge machine learning techniques to enhance the functionality of the Nuro Driver. As a pivotal member of the Prediction and Smart Agents team, your role will center on developing state-of-the-art models that predict the behavior of surrounding traffic, which are integral to our autonomous systems. These models will be utilized both on-board and off-board in realistic closed-loop simulations.In this position, you will delve into innovative machine learning approaches to address complex challenges in autonomous driving. Your work will involve employing generative sequence modeling techniques to accurately predict intricate, interactive traffic scenarios. This necessitates a deep understanding of the intentions of other road users and their impact on safe driving decisions. You will also explore diverse input modalities, including End-to-End (E2E) strategies, to forecast the behavior of other agents. A crucial aspect of this role is the creation of intelligent, controllable agents to facilitate effective closed-loop training within simulations.If you are driven by the challenge of solving complex problems, leading impactful research, and witnessing your contributions in real-world applications, we invite you to apply!About the WorkDesign and develop scalable, machine learning-based prediction systems to generate multi-modal, realistic, and kinematically feasible trajectories.Engage in pioneering research focused on generative sequence modeling and sequential decision-making, exploring areas such as:Scalable generative sequence modeling techniques.Modeling marginal, conditional, and joint distributions for interactive agents.Transformer-based encoder-decoder frameworks.Large generative models and diffusion techniques.Agent controllability through conditioning, guidance, and various methodologies.Collaborate closely with the Planning team to create realistic and controllable agents that enhance our simulation capabilities.

Waymo is at the forefront of autonomous driving technology, committed to becoming the world's most trusted driver. 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™. Our mission is to enhance mobility access while significantly reducing traffic-related fatalities. With over ten million rider-only trips powered by the Waymo Driver, we have accumulated extensive experience, having driven more than 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.The Waymo AI Foundations team is dedicated to creating machine learning solutions that tackle complex challenges in autonomous driving. Our goal is to ensure the safe operation of Waymo vehicles in various cities and under diverse driving conditions. We actively collaborate with other research teams within Alphabet, focusing on areas such as reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.This position follows a hybrid work schedule and reports directly to a Staff Research Scientist / Tech Lead Manager.

Waymo, the leader in autonomous driving technology, aims to be the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo is dedicated to developing the Waymo Driver—The World's Most Experienced Driver™—to enhance mobility access and significantly reduce traffic-related fatalities. With over ten million rider-only trips facilitated by our technology, which has autonomously navigated more than 100 million miles on public roads and countless simulations across more than 15 U.S. states, we are at the forefront of autonomous transportation.The Waymo Applied Research team is devoted to crafting machine learning solutions that tackle key challenges in autonomous driving, focusing on safely operating Waymo vehicles across diverse cities and under varying driving conditions. We thrive on collaboration, fostering partnerships with other research teams within Alphabet to push the boundaries of innovation.In this hybrid role, you will report to a Technical Lead Manager.

Waymo is at the forefront of autonomous driving technology, dedicated to becoming the most reliable driver in the world. Originating from the Google Self-Driving Car Project in 2009, we are committed to enhancing mobility access and preventing traffic-related fatalities. Our innovative Waymo Driver has successfully completed over ten million rider-only trips, leveraging extensive real-world experience with over 100 million miles driven autonomously and billions of miles simulated across more than 15 states.The Simulator Team at Waymo specializes in crafting advanced simulations that replicate realistic environments for the testing and training of the Waymo Driver. Comprising a diverse group of software engineers, machine learning experts, and data scientists, our team is focused on developing leading-edge simulation technologies powered by sophisticated ML algorithms to optimize the performance of the Waymo Driver. Our efforts include modeling real-world scenarios with realistic entities such as vehicles, pedestrians, cyclists, traffic systems, and various weather conditions.To enhance the realism and control of our simulations, we utilize state-of-the-art ML technologies, including large foundational World Models trained on our proprietary datasets and reinforcement learning techniques for long-term decision-making. We also invest in robust infrastructure that enables rapid setup and execution of multiple counterfactual scenarios for thorough testing of our autonomous driving systems.In this hybrid role, you will report to a Senior Staff Tech Lead Manager.

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.

Who We Are Nuro is a pioneering self-driving technology company dedicated to making autonomy accessible to everyone. Established in 2016, we are developing the most scalable autonomous driving solution, merging advanced AI with high-performance automotive hardware. Our flagship technology, the Nuro Driver™, is licensed for various applications including robotaxis, commercial fleets, and personal vehicles. With years of proven self-driving deployments, Nuro provides automakers and mobility platforms with a clear trajectory towards commercial-scale AVs, fostering a safer, more connected future. About the Role Join our learned behavior team where we leverage sophisticated machine learning strategies to expedite software advancements. This role involves close collaboration with software teams to identify challenges and implement innovative machine learning approaches to tackle real-world problems. Your work may include self-supervised learning for robust representation, out-of-distribution detection for addressing long-tail issues, refining reinforcement learning methods for motion planning, trajectory prediction, and enhancing model robustness to address uncertainties. If you are passionate about solving complex problems with practical solutions ready for vehicle deployment, we invite you to be a part of our journey! About the Work Develop scalable machine learning systems for planning and predicting safe, feasible trajectories for autonomous vehicles. Investigate generative sequence modeling and sequential decision-making; backgrounds in Embodied AI for robotics, Causal reasoning, Model interpretability, and Joint prediction and planning are advantageous. Address uncertainties arising from interconnected autonomous systems. Collaborate across autonomy teams to create comprehensive solutions for major autonomy challenges by understanding issues, proposing ideas, prioritizing tasks, and developing effective solutions. Implement practical solutions and deploy them on real-world vehicles. About You You possess extensive expertise and experience in one or more of the following areas: M.Sc. or Ph.D. in Computer Science, Artificial Intelligence, Mathematics, or a related discipline. Strong background in sequential decision-making, Imitation Learning, Deep Reinforcement Learning, generative modeling, and more.

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, striving to be the world's most trusted driver. Originating as 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 save countless lives that are lost to traffic accidents. The Waymo Driver powers our fully autonomous ride-hailing service and can be integrated into various vehicle platforms and applications. With over ten million rider-only trips completed and extensive experience gained from autonomously driving over 100 million miles on public roads and tens of billions of miles in simulation across more than 15 states, we are leading the way in transforming transportation.The Waymo Applied Research team is committed to pioneering machine learning solutions that tackle significant challenges in autonomous driving, with the ultimate aim of safely operating Waymo vehicles across numerous cities and diverse driving conditions. Our team actively initiates and nurtures collaborations with other research teams within Alphabet to drive innovation.In this hybrid role, you will report directly to a Technical Lead Manager.

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, our focus has been on developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and save lives currently lost in traffic incidents. With over ten million rider-only trips facilitated by our technology, and more than 100 million miles driven autonomously on public roads, we are transforming transportation across 15+ U.S. states.The Predictive Planning team (PrePlan) is responsible for designing and implementing advanced machine learning solutions that forecast future world states and plan the Waymo Driver’s actions. Our goal is to harness Waymo’s extensive driving data to create robust, adaptable, and efficient deep neural networks that empower our autonomous vehicles to navigate complex environments safely.In this hybrid position, you will collaborate closely with our PrePlan team and be matched with your team after completing onsite interviews.Your Responsibilities Will Include:Developing cutting-edge ML-driven prediction and planning systems to boost the capabilities of our ML driver and facilitate the rapid growth of Waymo’s services.Converting open-ended, real-life challenges into well-defined ML problems, researching and applying state-of-the-art ML techniques, such as foundation models and reinforcement learning, to enhance autonomous vehicle planning and prediction.Collaborating with top-tier researchers, engineers, and product managers to ensure safe and smooth planning behaviors for all road users, aligning with product specifications.Creating and assessing large-scale models, integrating them into Waymo’s production planning software for real-world applications in close cooperation with the Planner and Research teams.

Waymo is a pioneering technology company focused on autonomous driving, aiming to become the world’s most trusted driver. 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 and significantly reduce traffic-related fatalities. Our technology powers a fully autonomous ride-hailing service and can be integrated across various vehicle platforms and applications. The Waymo Driver has successfully completed over ten million rider-only trips, leveraging experience from over 100 million miles driven autonomously on public roads and billions more in simulation across more than 15 U.S. states.Our Software Engineering team designs the intelligent systems behind Waymo’s autonomous driving capabilities. Our software enables the Waymo Driver to sense its surroundings, make informed decisions, and transport passengers safely. We tackle intricate technical challenges in robotics, perception, decision-making, and deep learning, collaborating closely with hardware and systems engineers. If you are a passionate software engineer or researcher with curiosity for Level 4 autonomous driving, we want to connect with you.In this hybrid position, you will report to the Technical Lead Manager.

Waymo is at the forefront of autonomous driving technology, aspiring to be the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, our focus has been on developing the Waymo Driver—The World’s Most Experienced Driver™—aimed at enhancing mobility while significantly reducing traffic-related fatalities. Our autonomous driving technology powers Waymo’s fully autonomous ride-hailing service, with the Waymo Driver having completed over ten million rider-only trips, leveraging its extensive experience of more than 100 million miles driven autonomously on public roads and tens of billions of miles simulated across 15+ U.S. states.The Compute Team at Waymo is on a mission of critical importance. We are responsible for delivering the computing platform that operates our fully autonomous vehicle software stack. To meet this mission, we design high-performance custom silicon and develop system-level compute architectures that push the limits of performance, power efficiency, and latency. We collaborate closely across disciplines to ensure that our hardware and software designs achieve maximum efficiency and performance. We are seeking curious, talented individuals to join our multidisciplinary team to work on one of the highest performance automotive compute platforms in the world.This position follows a hybrid work model, and you will report directly to the Senior Staff Silicon Engineer.

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 developed the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access while significantly reducing traffic-related fatalities. The Waymo Driver powers our fully autonomous ride-hail service and is adaptable for various vehicle platforms and applications. With over ten million successful rider-only trips and more than 100 million miles driven autonomously on public roads, complemented by tens of billions of miles in simulation across 15+ U.S. states, we are transforming the future of transportation.The Perception team is pivotal in developing the system that learns spatial-temporal representations and their semantic meanings in the environment surrounding our autonomous driving vehicles (ADVs). We collaborate closely with downstream teams for optimization and integration into the Waymo Driver and conduct our own research to tackle real-world challenges. Access to extensive driving data from a variety of sensors enables our engineers to (1) create methods for continuous learning from large-scale real-world data, (2) develop scalable models and model training strategies, (3) analyze real-world behaviors and create systems to handle complex real-world interactions, and (4) optimize models for both 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, our focus has been on creating the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and prevent traffic-related fatalities. With our Waymo Driver, we have powered a fully autonomous ride-hail service, achieving over ten million rider-only trips and accumulating experience from over 100 million miles driven on public roads and tens of billions of miles in simulation across more than 15 U.S. states.The Waymo AI Foundations team is on a mission to create machine learning solutions that address critical challenges in autonomous driving, aiming to operate Waymo vehicles safely across numerous cities and under various driving conditions. We actively engage in collaborative efforts with other research teams within Alphabet, focusing on areas such as reinforcement learning, learning from demonstrations, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.This role follows a hybrid work schedule and you will report to a Senior Staff Software Engineer.

Waymo, a leader in autonomous driving technology, aims to be the most trusted driver in the world. Originating from the Google Self-Driving Car Project in 2009, our mission is to create the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and reduce traffic fatalities. The Waymo Driver powers our fully autonomous ride-hail service and can be integrated across various vehicle platforms and applications. With over ten million rider-only trips and more than 100 million miles driven autonomously on public roads, we are pioneering the future of transportation.As part of our Product Data Science team, you will collaborate with Engineering, Product, and Operations to leverage data for informed decision-making. We tackle high-impact projects, from quality assurance and operational efficiency to market analysis and rider satisfaction. Our data-driven, inquisitive, and adaptable approach is essential for scaling the Waymo Driver safely and effectively.This position follows a hybrid work model and you will report to the Product Data Science Lead.

About Nuro Nuro is pioneering self-driving technology with a vision to democratize autonomy for everyone. Established in 2016, we are developing the most scalable driver in the world, integrating advanced AI with automotive-grade hardware. Nuro's core technology, the Nuro Driver™, is licensed for diverse applications ranging from robotaxis and commercial fleets to personal vehicles. With years of successful self-driving deployments under our belt, we offer automakers and mobility platforms a clear pathway to achieving commercial-scale autonomous vehicles, contributing to a safer, richer, and more connected future. Role Overview At Nuro, we adopt a machine learning-first approach to autonomous driving. The quality of our Nuro Driver™ is intrinsically linked to the data utilized for its training, and this position plays a pivotal role in maintaining that standard. As a Senior Project Manager in ML Operations, your focus will be on oversight rather than execution. While our operators manage the day-to-day operations of data pipelines, your responsibility will be to take a broader view, identifying where quality issues may arise, understanding the causes, and devising actionable solutions. You will co-manage over 10 active data labeling pipelines in collaboration with senior leadership, placing a strong emphasis on data quality and addressing any gaps. This role requires a keen eye for detail, as even minor errors in annotation or classification can lead to significant safety regressions. We seek an individual who prioritizes precision and can differentiate between labeling mistakes and systemic issues. Your Responsibilities Establish and uphold data quality standards across 10+ labeling pipelines, defining what constitutes “good” for each data type, implementing measurement tools, and meticulously tracking discrepancies. Identify and rectify quality gaps by auditing live workflows, querying databases, tracing accuracy failures to their root causes, and presenting specific, evidence-based improvement plans. Work collaboratively above the execution layer by partnering with operations project managers focused on throughput and delivery, providing insights into quality diagnostics that they may overlook.