Machine Learning Engineer - Perception

Waymo is pioneering the future of autonomous driving technology with a commitment to becoming the most trusted driver worldwide. Since its inception as the Google Self-Driving Car Project in 2009, Waymo has dedicated itself to developing the Waymo Driver—The World’s Most Experienced Driver™—with the goal of enhancing mobility access and saving countless lives currently 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 applications. Having completed over ten million rider-only trips and autonomously navigated more than 100 million miles on public roads, our technology has undergone extensive testing, including tens of billions of miles in simulations across more than 15 U.S. states.The Simulator Team at Waymo specializes in creating cutting-edge simulations of realistic environments designed for the rigorous testing and training of the Waymo Driver. Our diverse and collaborative team comprises software engineers, machine learning (ML) engineers, and data scientists, all united in our mission to develop industry-leading simulation solutions utilizing advanced ML algorithms to measure and enhance the Waymo Driver's performance. By leveraging machine learning, we meticulously model real-world scenarios, including realistic agents such as vehicles, pedestrians, cyclists, motorcyclists, roads, traffic control systems, and varying weather conditions.To enhance the fidelity and steerability of our simulations, we integrate the latest ML technologies, including large foundation models trained on our exclusive datasets and advanced diffusion techniques. Our investment in robust infrastructure facilitates the swift setup and deployment of multiple scenarios for comprehensive testing of our autonomous driving systems.In this hybrid role, you will report to a Senior Engineering 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, Waymo has developed the Waymo Driver—The World’s Most Experienced Driver™—aiming to enhance mobility access while significantly reducing road traffic fatalities. The Waymo Driver powers our fully autonomous ride-hail service and is adaptable to various vehicle platforms and use cases. With over ten million rider-only trips and the experience of driving autonomously over 100 million miles on public roads, coupled with tens of billions of miles in simulation across more than 15 U.S. states, we are redefining transportation.The Simulator Team at Waymo is tasked with creating cutting-edge simulations of realistic environments to rigorously test and train the Waymo Driver. Our diverse and collaborative team comprises software engineers, machine learning engineers, and data scientists dedicated to developing industry-leading simulation solutions using advanced machine learning algorithms to elevate the Waymo Driver’s performance. By harnessing the power of machine learning, we replicate real-world scenarios, including vehicles, pedestrians, cyclists, traffic control systems, and weather conditions.To enhance the fidelity and steerability of our simulations, we utilize the latest machine learning technologies, such as large foundational World Models trained on our datasets, world understanding and reasoning capabilities for edge cases, and reinforcement learning for long-term credit assignment. We also invest in robust infrastructure that allows us to rapidly set up and deploy 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.

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

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

About Us Nuro is a pioneering self-driving technology firm focused on democratizing autonomy for everyone. Established in 2016, we are on a mission to create the world's most scalable autonomous driver. Our innovative approach blends advanced AI with automotive-grade hardware, allowing us to license our core technology, the Nuro Driver™, across diverse applications including robotaxis, commercial fleets, and personal vehicles. Our proven technology, tested through numerous self-driving deployments, provides automakers and mobility platforms with a clear path to commercial-scale autonomous vehicles, fostering a safer, more connected future. Position OverviewWe are excited to expand our robotics team and are seeking a talented Senior Software Engineer to join our Sensor Data and Calibration unit. The ideal candidate will possess a strong background in robotics and machine learning, with a focus on developing sophisticated synthetic sensor simulation models and algorithms. Experience in research, development, and application of machine learning techniques (such as NeRF or Gaussian splatting) for generating synthetic sensor data, including photorealistic images and realistic LiDAR or radar outputs, is essential. Key Responsibilities Research and create cutting-edge synthetic sensor simulation methodologies. Evaluate and characterize the realism and effectiveness of synthetic sensor data. Address essential inquiries regarding sensor data and autonomous performance. Collaborate with various teams across autonomy, infrastructure, and systems to define mapping requirements. Qualifications One of the following: PhD in machine learning, computer science, electrical engineering, robotics, or a related field, with 3+ years of industry experience. Master's degree with 4+ years of industry experience. 5+ years of industry experience. In-depth knowledge of machine learning fundamentals with practical experience in training and assessing contemporary ML models. Proficient in Python, with experience in deep learning frameworks such as PyTorch, TensorFlow, or JAX. Preferred Qualifications Strong grasp of 3D geometry and state estimation principles. Experience in systems-level coding. Familiarity with simulating and modeling real sensors (camera, LiDAR, radar, IMU, etc.), including noise modeling. Expertise in modern ML graphics techniques, such as NeRF, Gaussian Splatting, and/or generative models.

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

Waymo is 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.

Waymo is at the forefront of autonomous driving technology, dedicated to becoming the most trusted driver on the planet. Originally initiated as the Google Self-Driving Car Project in 2009, Waymo has relentlessly pursued the development of the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access while aiming to save lives lost in traffic accidents. The Waymo Driver powers our fully autonomous ride-hailing service and can be adapted to various vehicle platforms and applications. With over ten million rider-only trips and an impressive record of over 100 million miles driven autonomously on public roads, along with tens of billions of miles simulated across 15+ U.S. states, Waymo is leading the charge in safe and effective autonomous transportation.The Simulator Team at Waymo is tasked with creating cutting-edge simulations of realistic environments that are crucial for testing and training the Waymo Driver. Our team consists of a diverse group of software engineers, machine learning engineers, and data scientists, dedicated to developing industry-leading simulation solutions that assess and enhance the performance of the Waymo Driver. By accurately modeling the real world—including self-driving vehicle dynamics, realistic agents (vehicles, pedestrians, cyclists, motorcyclists), traffic systems, and environmental conditions—we ensure that our simulations reflect true driving scenarios. This capability is essential to our mission of creating the world's most experienced driver.The Vehicle and Automated Driving Realism team is focused on innovating tools and techniques that enhance driving realism, a core aspect of our simulation efforts. We are committed to ensuring that the data derived from our simulations accurately represents real-world driving performance, emphasizing performance, reliability, fidelity, and usability.In this role, you will report directly to a Senior Staff Engineering Manager.

At Waymo, we are pioneering the future of autonomous driving technology with a mission to become the world’s most trusted driver. Originating from the Google Self-Driving Car Project in 2009, our focus is on developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and prevent the tragic loss of lives due to traffic accidents. The Waymo Driver not only powers our fully autonomous ride-hailing service but is also adaptable to various vehicle platforms and use cases. With over ten million trips completed and more than 100 million miles driven autonomously on public roads, we are setting the standard in the industry.The Simulator Team at Waymo is dedicated to creating advanced simulations that replicate realistic environments for the testing, training, and validation of the Waymo Driver. Our diverse and collaborative group of machine learning (ML) engineers, software engineers, and ML research engineers develop cutting-edge simulation solutions that utilize sophisticated generative and reconstructive ML algorithms. These simulations model real-world scenarios, including realistic agents, roads, traffic systems, weather conditions, and an extensive sensor suite (Camera, Lidar, Radar).In this position, you will play a crucial role in enhancing the fidelity, scalability, and richness of our simulations. By leveraging state-of-the-art ML technologies and large-scale datasets, you will help create dynamic virtual worlds that directly influence the development and validation of the Waymo Driver.In this role, you will report to a Senior Staff Engineering Manager.

At Waymo, we are pioneers in autonomous driving technology, dedicated to becoming the world's most trusted driver. Since our inception as the Google Self-Driving Car Project in 2009, we have been committed to advancing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and prevent traffic-related fatalities. Our Waymo Driver drives our fully autonomous ride-hailing service and is adaptable to various vehicle platforms and applications. With over ten million rider-only trips facilitated and experience from over 100 million miles on public roads and tens of billions in simulation across more than 15 U.S. states, we are at the forefront of this technological revolution.The Simulator Team at Waymo is tasked with creating cutting-edge simulations of realistic environments for the rigorous testing and training of the Waymo Driver. Our diverse and collaborative team consists of software engineers, machine learning (ML) engineers, and data scientists, all focused on developing industry-leading simulation solutions utilizing advanced ML algorithms that assess and enhance the Waymo Driver’s performance. We model the real world in detail, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists), roads, traffic control systems, weather conditions, and a comprehensive sensor suite featuring cameras, LiDAR, and radars.In this hybrid role, you will report to a Senior Engineering Manager.Your Responsibilities:Design and develop robust C++ software systems and infrastructure for our realistic world generation platform, ensuring seamless integration with downstream Waymo applications.Collaborate closely with simulation, onboard, and system engineers, as well as data scientists to drive critical milestones for Waymo.Monitor, enhance, and ensure the performance, scalability, testing, and reliability of our platform.Engage with fellow engineers to architect the long-term vision of the system.

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

Waymo is at the forefront of autonomous driving technology, dedicated to becoming the most trusted driver in the world. Initiated as the Google Self-Driving Car Project in 2009, Waymo has relentlessly focused on developing the Waymo Driver—The World's Most Experienced Driver™—to enhance mobility access and save countless lives currently lost in traffic accidents. The Waymo Driver is the driving force behind our fully autonomous ride-hailing service and is adaptable across various vehicle platforms and product applications. With over ten million rider-only trips completed, our technology has driven more than 100 million miles on public roads and achieved tens of billions of miles in simulation across over 15 U.S. states.The Simulator Team at Waymo crafts cutting-edge simulations of realistic environments for testing and training the Waymo Driver. You will be part of a diverse and collaborative group of machine learning (ML) engineers, software developers, and data scientists. Together, we develop industry-leading simulation solutions utilizing advanced ML algorithms to measure and enhance the Waymo Driver's performance. Our work involves joint modeling of the real world, incorporating realistic agents (vehicles, pedestrians, cyclists, motorcyclists), roads, traffic control systems, weather conditions, and a comprehensive sensor suite including cameras, LiDAR, and radars.To boost the fidelity, scalability, and controllability of our simulations, we leverage the latest ML technologies such as large language models, foundational world models, and reconstructive methods trained on extensive datasets, alongside traditional rendering techniques.In this dynamic hybrid role, you will report to a Senior Staff Engineering Manager.Your Responsibilities:Innovate and Develop: Collaborate with our elite research engineering team to spearhead innovation in ultra-realistic sensor data and perception simulation for autonomous vehicles. You will implement the latest simulation technologies using 3D Gaussian Splatting, foundational models for sensor data, and traditional 3D graphics.Lead and Scale: Oversee the deployment and scaling of sensor simulation to tackle some of Waymo's most challenging problems. You will engage in a highly cross-functional environment, working alongside research, systems engineering, and other teams to expedite company objectives.Transfer Research to Production: Collaborate closely with Waymo's foundational AI research team to translate cutting-edge research into scalable, production-ready solutions.

Be Part of the Future of Home RoboticsAt Sunday Robotics, we are pioneering the development of personal robots that alleviate the burden of repetitive household tasks. Our mission is to democratize access to advanced robotics, allowing families to reclaim precious time.After an intensive 18 months of assembling a talented team, securing funding, and validating our innovative technology, we are eager to welcome passionate individuals to join us as we embark on the next exciting chapter of our journey. If you are enthusiastic about contributing your skills to the cutting edge of robotics, we want to hear from you!The RoleAs a Machine Learning Infrastructure Engineer at Sunday Robotics, you will play a pivotal role in shaping the future of home robotics. You will develop end-to-end machine learning models for robotic manipulation, creating foundational systems that will expedite our efforts to introduce robots into everyday homes.This versatile position can be customized to align with your specific expertise, whether it be in data pipelines, training infrastructure, or inference. Your contributions will span the entire robot learning pipeline: from ingesting and processing multimodal data to scaling distributed training, optimizing real-time inference, and developing research tools.What You Will AccomplishEnhance the research codebase for optimal ergonomics and rapid iteration.Oversee model training infrastructure, including job scheduling, checkpointing, metrics, and logging.Facilitate distributed training across GPU clusters with minimal friction for researchers.Enable the training of larger models through techniques such as sharding and memory optimization.Profile and enhance GPU utilization, memory efficiency, and training throughput.Create low-latency inference pipelines for real-time robot control, employing techniques to optimize performance.Collaborate closely with researchers and roboticists to transform research requirements into robust software and infrastructure.Data Pipelines and Research ToolsArchitect high-throughput pipelines for the ingestion, validation, and transformation of multimodal robot data such as video and proprioception.Develop efficient storage systems and metadata indexing for seamless data retrieval.

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 been relentlessly focused on creating the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and prevent traffic-related fatalities. The Waymo Driver is the driving force behind our fully autonomous ride-hail service, optimized for various vehicle platforms and applications. With over ten million rider-only trips and more than 100 million miles driven autonomously on public roads, alongside tens of billions of simulated miles across 15+ U.S. states, Waymo is redefining transportation.The ML Platform team at Waymo plays a critical role by offering a suite of tools that facilitate and automate the entire machine learning workflow lifecycle, including feature and experiment management, model development, optimization, and monitoring. Our initiatives have made machine learning more accessible across diverse teams at Waymo, including Perception, Planner, Research, and Simulation.We are seeking talented engineers with expertise in machine learning software or systems to enhance compute performance both in the cloud and on vehicles. You'll engage with the entire ML stack from a systems perspective, tackling challenges such as efficient deep learning models, model compression, and improving ML software (e.g., JAX, XLA, Triton, and CUDA). This hybrid position reports directly to the Senior Manager of Runtime and Optimization.

Join Coupang as the Director of Machine Learning Engineering and lead transformative projects that will redefine customer experiences. You will spearhead our machine learning initiatives, collaborating with cross-functional teams to drive innovative solutions across our e-commerce platform.Responsibilities include:Developing and implementing cutting-edge machine learning algorithms.Leading a team of data scientists and engineers.Collaborating with stakeholders to identify opportunities for leveraging data to enhance customer satisfaction.To apply, please complete the Internal Transfer Request Form using your Coupang email address.

About NewsBreakEstablished in 2015, NewsBreak is a pioneering Content Intelligence platform redefining the content economy. With a robust user base of over 40 million monthly active users, our flagship platform delivers tailored local news and information, powered by cutting-edge AI, recommendation systems, and advanced adtech.Acknowledged by Fast Company as #32 among the Top Workplaces for Innovators, we proudly hold Great Place to Work® certification and foster a vibrant team of technologists, product innovators, and business leaders dedicated to addressing significant challenges at scale.Achieving unicorn status in 2021, we remain steadfast in our commitment to high growth, seeking the ideal team to realize our mission: to establish the foundational infrastructure for content intelligence.If you’re driven to dream big, innovate rapidly, and make a meaningful impact, we want to hear from you! For more details, visit www.newsbreak.com/aboutAbout the Role:We are seeking a Machine Learning Infrastructure Engineer to join us in building the pivotal infrastructure that trains, serves, and monitors the models behind our Ads and Recommendations products. You will be part of a small, high-responsibility team that implements platform enhancements end-to-end—collaborating with product and data teams to minimize latency and costs while expediting the transition from concept to safely launched model.Your role will encompass the entire ML lifecycle: enhancing training efficiency and reliability, optimizing model serving performance, and fortifying our feature/embedding platform to ensure models remain current and consistent across offline and online applications. We are looking for someone who takes genuine ownership, completes tasks, and elevates the standards for stability and developer experience.Why This Role:Scope & Impact: Join a small team with a significant influence—your contributions will directly impact production.Ownership: Manage everything from design to rollout and post-launch insights; enjoy real autonomy with support.Growth: Gain visibility across the stack and a clear pathway to lead projects and mentor others.Pragmatic Culture: We prioritize outcomes over jargon, valuing clear thinking and follow-through.

Who We AreAt Ema, we are pioneering cutting-edge AI technologies designed to enhance the creativity and productivity of employees across enterprises. Our unique technology enables organizations to entrust Ema, the AI employee, with repetitive tasks, freeing up human talent for more strategic initiatives. Founded by a team of former executives from tech giants such as Google, Coinbase, and Okta, and backed by prestigious investors including Accel Partners and Naspers, we are on the forefront of the AI revolution.Our diverse team, composed of top engineers from leading tech firms like Microsoft Research and Facebook, brings a wealth of knowledge and experience, primarily from renowned institutions such as Stanford and MIT. Operating out of Silicon Valley and Bangalore, India, we embrace a hybrid work model, requiring employees to be in our Mountain View, CA office three days a week.Who You AreWe seek passionate and innovative Machine Learning Engineers who thrive on tackling complex challenges and enjoy working with vast datasets. You have a talent for translating theoretical concepts into practical, scalable solutions, and you are a collaborative team player who excels in autonomous settings. Your enthusiasm for employing machine learning techniques, particularly in Natural Language Processing and Information Retrieval, is matched only by your desire to contribute to a mission-driven, high-growth startup making a significant impact.Your ResponsibilitiesDesign, develop, and deploy machine learning models that drive our NLP, retrieval, ranking, reasoning, dialog, and code-generation systems.Implement state-of-the-art machine learning algorithms, including Transformer-based models and reinforcement learning, to enhance AI system performance.Analyze and process large, complex datasets (structured, semi-structured, and unstructured) to inform model development.Engage throughout the entire machine learning model lifecycle, from problem identification and data exploration to feature engineering and model evaluation.

About EarnInEarnIn is a trailblazer in the field of earned wage access, dedicated to creating innovative solutions that provide real-time financial flexibility for individuals navigating the challenges of living paycheck to paycheck. Our community empowers members to access their earnings as they earn them, offering options to spend, save, and invest without mandatory fees, interest charges, or credit inquiries.With a highly experienced leadership team and backing from esteemed partners such as A16Z, Matrix Partners, DST, and Ribbit Capital, EarnIn is in a strong position with a thriving core business and significant growth potential. We are rapidly expanding and eager to onboard world-class talent to help us shape the future of our organization.POSITION SUMMARYWe are looking for a forward-thinking and experienced Director of Machine Learning to spearhead our machine learning initiatives across the organization. As a fintech leader, machine learning is central to our business strategy and enhances user experience. We rely on advanced, scalable ML systems to make impactful decisions and provide outstanding customer value. Our goal is to revolutionize success stories through the application of generative AI and cutting-edge machine learning algorithms, resulting in significant business and societal outcomes.The Director of ML will prioritize operational excellence by crafting and executing a strategy that transitions ML models from research to production, ensuring optimal performance, reliability, and maintainability. The ideal candidate will have a demonstrated history of deploying ML models at scale, particularly in dynamic startup settings. A strong coding background, familiarity with production-level ML engineering, and the ability to connect theoretical frameworks with practical execution are essential.The base salary range for this full-time role in Mountain View is $414,000 to $506,000, accompanied by equity and benefits. Salary ranges are determined by role, level, and location. This is a hybrid position, requiring in-office work two days a week.

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.