Senior Applied Research Scientist in Perception

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.

Join Waymo as an Applied Research Scientist focusing on Perception LLM/VLM technologies. In this role, you will contribute to cutting-edge research and the development of advanced algorithms that enhance our self-driving technology.

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.

Join LinkedIn as a Senior Staff Applied Scientist specializing in Infrastructure Data Science. In this pivotal role, you will leverage your expertise to drive innovation and enhance the efficiency of our infrastructure systems. You will collaborate with cross-functional teams, developing cutting-edge data solutions that significantly impact our global user base.Your responsibilities will include conducting advanced data analyses, modeling complex systems, and implementing machine learning algorithms to optimize performance. You will also mentor junior scientists and contribute to a vibrant research culture, ensuring that LinkedIn remains at the forefront of technology and data science.

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 is seeking a highly skilled Senior Research Scientist to join our innovative team focused on sensor simulation. In this role, you will be responsible for developing cutting-edge simulation technologies that enhance our autonomous vehicle systems.Your expertise will contribute to improving the accuracy and efficiency of our simulations, playing a crucial role in the advancement of self-driving technology. You will collaborate with cross-functional teams to drive innovation and ensure our systems are at the forefront of the industry.

About Us:Aeva is at the forefront of perception technology, revolutionizing a myriad of industries including automated driving, industrial robotics, consumer electronics, consumer health, and security. Our mission is to pioneer the next generation of perception technologies, integrating essential LiDAR components into a compact silicon photonics chip. Our cutting-edge 4D LiDAR sensors offer unique capabilities, such as instant velocity detection alongside 3D positioning, empowering autonomous devices like vehicles and robots to make smarter, safer decisions.Role Overview:We are seeking a passionate and experienced Senior Perception Engineer to enhance our classical perception algorithms stack. As a critical member of our dynamic team, you will delve into the capabilities of Aeva’s 4D FMCW LiDARs, pushing the boundaries of autonomous driving performance further than ever before.

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.

As a Senior Software Engineer specializing in Perception Verification at Waymo, you will play a crucial role in enhancing the safety and performance of autonomous driving technology. Your expertise will guide the development of innovative algorithms and systems that validate perception capabilities, ensuring our vehicles can navigate the complexities of real-world environments.This position offers an exciting opportunity to work at the forefront of technology, collaborating with a talented team of engineers and researchers dedicated to revolutionizing transportation.

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 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.

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.

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, dedicated to becoming the world's most trusted driver. Originating as the Google Self-Driving Car Project in 2009, our mission is to enhance mobility access and save lives through innovative solutions. The Waymo Driver—The World’s Most Experienced Driver™—powers our fully autonomous ride-hail service and adapts to various vehicle platforms and use cases. With over ten million rider-only trips and 100 million miles driven autonomously on public roads, we are transforming the future of transportation.We are on the lookout for a seasoned Technical Lead Manager (TLM) to spearhead our Vehicle Understanding team. In this pivotal role, you will oversee production modules related to Vehicle Understanding for the Waymo Driver, focusing on vehicle classification, states, and intents. This position is crucial for Waymo's expansion both domestically and internationally, allowing you to make a significant impact and drive innovative changes that enhance the generalizability of the Waymo Driver.In this hybrid position, you will report directly to our Senior Staff TLM of Semantics Understanding.

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.

Join Nuro as a Senior Software Engineer specializing in Perception Data Infrastructure. In this pivotal role, you will be responsible for developing and optimizing systems that process perception data, enabling our autonomous vehicles to navigate safely and efficiently. You will collaborate with cross-functional teams to enhance our data infrastructure, ensuring reliability and scalability.

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.

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 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.