Research Scientist in Prediction & Planning

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.

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.

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.

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, 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.

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

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, 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 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.

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.

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, 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.

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 applications, including robotaxis, commercial fleets, and personal vehicles. Proven through extensive self-driving deployments, Nuro provides automakers and mobility platforms a clear pathway to commercial-scale autonomous vehicles, paving the way for a safer, more connected future. Role Overview As a Senior Machine Learning Research Scientist in our Perception & Behavior team, you will harness cutting-edge machine learning research to tackle complex real-world robotics challenges. Your primary focus will be on advancing the ML landscape and large-scale learning applications for autonomous vehicles, steering towards a holistic end-to-end driving system. This role involves developing and refining large-scale models for perception and behavior, staying abreast of the latest architectural innovations, collaborating with cross-functional teams to assess data and infrastructure needs, and enhancing model optimization and inference speeds. Your expertise in applied research will be critical in the creation and deployment of ML models within our autonomous vehicles. If you're passionate about solving fundamental AI challenges and seeing your solutions come to life in real-world robotics, we invite you to join our team! Key Responsibilities Develop and enhance state-of-the-art end-to-end ML models for autonomous vehicles, processing raw sensor data (camera, LiDAR, radar) to inform vehicle behavior. Rapidly prototype and iterate on solutions using extensive real-world driving datasets and robust computational resources. Investigate and implement innovative solutions to tackle some of the most pressing issues in AV technology, including handling rare events, ensuring safety, and providing comfortable user experiences. Collaborate closely with autonomy teams to identify critical challenges and devise comprehensive solutions through learned approaches. Partner with infrastructure, data, and evaluation teams to create efficient data handling, training, assessment, and validation processes. Deliver practical, high-performance solutions that can be deployed to the NuroDriver in live environments.

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, we have focused on developing the Waymo Driver—The World’s Most Experienced Driver™—aimed at enhancing mobility access and 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 rides completed, our technology has autonomously driven more than 100 million miles on public roads and tens of billions of miles in simulation across 15+ U.S. states.The Predictive Planning team (PrePlan) is responsible for crafting and implementing cutting-edge machine learning solutions that forecast future scenarios and dictate the Waymo Driver's actions. Our goal is to harness Waymo’s vast driving data to create robust, generalizable, and high-performing deep neural networks, allowing our autonomous vehicles to navigate intricate environments safely and efficiently.In this hybrid role, you will collaborate closely with our PrePlan team under the guidance of a dedicated manager, with the team assignment occurring post-on-site interviews.

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.

OverviewAt Google DeepMind, we believe that Artificial Intelligence is one of the most transformative inventions for humanity. Our team comprises scientists, engineers, and machine learning specialists dedicated to advancing cutting-edge AI technologies for the benefit of society and scientific progress, with a strong emphasis on safety and ethical considerations.The Gemini Safety team is responsible for ensuring the safety and fairness of our latest Gemini models. We are seeking a Research Scientist who will leverage data and innovative algorithms to enhance the performance of our user-oriented models. This role demands a fast-paced, highly collaborative work environment where support and teamwork are paramount.About UsGoogle DeepMind is at the forefront of AI innovation, focusing on using our technologies for meaningful public impact and exploring scientific frontiers. We work closely with various partners to tackle significant challenges while prioritizing ethical standards and safety protocols.Position OverviewWe are in search of a dynamic Research Scientist who excels in both exploring novel research inquiries and implementing technical solutions. Our team's mission is to enhance the safety and fairness of state-of-the-art AI models, contributing foundational technology to multiple product areas including Gemini App, Cloud API, and Search.Key Responsibilities:Optimize post-training and instruction tuning of state-of-the-art LLMs across various modalities including text-to-text and image/video/audio-to-text.Investigate data-driven, reasoning, and algorithmic strategies to ensure Gemini Models remain safe, highly effective, and accessible to all users.Enhance Gemini’s resilience against adversarial threats, particularly concerning high-risk abuse scenarios.Develop and uphold high-quality evaluation protocols to identify model behavior gaps and opportunities related to safety and fairness.Create and implement experimental plans to bridge identified gaps or develop new capabilities.Foster innovation and deepen our understanding of Supervised Fine Tuning and Reinforcement Learning fine-tuning at scale.

About UsAt Aurora Innovation, we are dedicated to safely and efficiently delivering the transformative power of self-driving technology to everyone. Our mission is to create a future where mobility is accessible and efficient for all.Discover The Aurora Driver and join us in ushering in a new era of mobility and logistics that prioritizes safety, efficiency, and accessibility.At Aurora, you'll collaborate with brilliant minds to solve intricate challenges, enhancing your expertise while expanding your horizons. For the latest updates, visit aurora.tech or follow us on LinkedIn.We welcome talented individuals from diverse backgrounds eager to contribute to building a safer transportation ecosystem that ensures timely delivery of essential goods while enhancing mobility efficiency. We are currently looking for a Machine Learning Engineering Team Lead to join our Behavior Planning Team. This pivotal role places you at the cutting edge of autonomous vehicle technology. You will not only utilize AI and ML methods but also push the boundaries of how self-driving systems perceive their environment, engage with road users, and execute intricate, high-dimensional decision-making.

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.