Senior Staff Machine Learning Engineer, Simulation

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

Waymo is 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.

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 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 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.

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

Join our dynamic team at Moveworks as a Senior Staff Machine Learning Engineer. In this pivotal role, you will leverage your expertise in machine learning and artificial intelligence to develop and enhance agentic systems that transform the way organizations interact with their customers. You will work alongside a talented group of engineers and data scientists to create innovative solutions that improve user experiences.

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.

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

Waymo 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 world's most trusted driver. Originating as the Google Self-Driving Car Project in 2009, Waymo has developed the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and save thousands of lives currently lost to traffic accidents. The Waymo Driver operates Waymo’s fully autonomous ride-hail service and is adaptable to various vehicle platforms and use cases. With over ten million rider-only trips, our technology has autonomously driven more than 100 million miles on public roads and processed tens of billions of miles in simulation across more than 15 U.S. states.The Waymo ML Frameworks & Efficiency team collaborates closely with Research and Production teams to design and implement models in Perception and Planning, which are essential components of our autonomous driving software. We provide our partners with the most effective frameworks for the entire model development lifecycle and innovative efficiency solutions for model execution, tailored to the unique challenges of machine learning in autonomous driving.We are seeking talented engineers with expertise in ML frameworks or ML systems to enhance computational efficiency in both cloud environments and vehicle systems. You will engage with the entire ML stack, from deep learning model architectures to accelerator runtimes, working alongside ML modeling teams to drive large-scale efficient model training and inference.

Waymo is at the forefront of autonomous driving technology, dedicated to becoming the world’s most trusted driver. Originating as the Google Self-Driving Car Project in 2009, Waymo has tirelessly developed the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and save lives lost to traffic accidents. The Waymo Driver powers our fully autonomous ride-hailing service, and its technology can be adapted to a variety of vehicle platforms and applications. With over ten million rider-only trips and extensive experience driving over 100 million miles on public roads, alongside tens of billions of miles in simulation across more than 15 U.S. states, our capabilities are unparalleled.The Perception team is integral to Waymo, developing the advanced technology that enables the Waymo Driver to accurately perceive its surroundings, make timely decisions, and ensure safe transportation for passengers. We are engaged in cutting-edge research that addresses tangible challenges and fosters collaboration with research teams at Alphabet. With access to vast amounts of driving data from diverse sensors, we empower machine learning practitioners to create multi-modal models and techniques on a grand scale.In this hybrid role, you will report directly to the Director of Engineering.

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

Coupang is looking for a Staff Machine Learning Engineer in Mountain View to help strengthen its e-commerce platform. This position centers on applying advanced machine learning methods to improve both user experience and internal operations. Role overview The Staff Machine Learning Engineer will work closely with teams across the company to design, build, and launch machine learning models. These efforts aim to solve complex business challenges and support Coupang’s growth. Key responsibilities Develop and implement machine learning models that enhance system performance Collaborate with cross-functional groups to identify and address business needs Contribute to the deployment and ongoing improvement of machine learning solutions Location This role is based in Mountain View, USA.

Join Our TeamAre you passionate about pioneering projects that harness advanced AI technology to unlock significant benefits from meetings and conversations? Become a vital member of our core AI team at Otter.ai, where you will collaborate with seasoned scientists and engineers dedicated to machine learning. As a Senior Machine Learning Engineer, your expertise in software engineering will be crucial in scaling and refining our machine learning systems. You will play a key role in transforming innovative research into production-ready features that enhance Otter’s summarization and conversational intelligence products.Your ContributionsDesign, construct, and advance extensive SID / ASR / NLP / LLM systems that drive essential product experiences, including summarization, chat, and speech comprehension for millions of interactions.Lead the creation and execution of training, fine-tuning, post-training, and inference methodologies for large language and speech models utilizing PyTorch and/or JAX while balancing quality, latency, cost, and dependability.Innovate and enhance model architectures, loss functions, decoding techniques, and training methodologies for speech and language models, guided by research insights and production restrictions.Oversee the entire ML system lifecycle, from initial research prototyping to production deployment, continuous monitoring, iteration, and long-term maintenance.Collaborate closely with product and infrastructure teams to translate groundbreaking research into scalable, production-grade systems that yield measurable user and business outcomes.Champion system-level enhancements in model performance, robustness, observability, and operational excellence using real-world conversational data.Establish technical direction and best practices for ML infrastructure, data pipelines, evaluation frameworks, and deployment workflows within a cloud environment.Diagnose and resolve complex issues related to model behavior, data quality, scalability, and system interactions, often preemptively before they affect users.Mentor and uplift fellow engineers, contributing to team standards, evaluating designs, and fostering a culture of sound technical decision-making and execution.

Waymo is a pioneering autonomous driving technology firm dedicated to becoming the world’s most reliable driver. Originating as the Google Self-Driving Car Project in 2009, Waymo has committed itself to developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access while aiming to save thousands of lives lost in traffic accidents. The Waymo Driver underpins Waymo’s fully autonomous ride-hailing services and can be adapted across various vehicle platforms and applications. With more than ten million rider-only trips completed, it has driven over 100 million miles on public roads and tens of billions of miles in simulations across 15+ U.S. states.In this hybrid role, you will work closely under the guidance of a Technical Lead in Planner Technology.Your Responsibilities:Analyze driving behavior issues from logs to identify underlying causes.Enhance the performance of cutting-edge machine learning models in the Planner.Build foundational frameworks to further the capabilities of the Waymo Driver.Broaden the influence of machine learning models while maintaining interpretability and behavioral assurances.Contribute to solving some of the most complex driving scenarios.

At Waymo, we are pioneering the future of autonomous driving technology with an unwavering commitment to becoming the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, our focus has always been on engineering the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and drastically reduce traffic-related fatalities. The Waymo Driver currently powers our fully autonomous ride-hail service, having completed over ten million rider-only trips and covering more than 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.This role in Software Engineering is crucial as we develop the intelligent systems that allow the Waymo Driver to navigate complex environments, make sound decisions, and ensure safe transportation for our users. We tackle intricate technical challenges in robotics, perception, decision-making, and deep learning, collaborating closely with hardware and systems engineers. If you are a dedicated software engineer or researcher with a passion for Level 4 autonomous driving, we are eager to meet you.In this hybrid role, you will report directly to a Technical Lead Manager.

Who We Are Nuro is a pioneering self-driving technology company dedicated to making autonomy accessible to everyone. Established in 2016, Nuro is revolutionizing transportation with the most scalable autonomous driver, integrating advanced AI with automotive-grade hardware. Our flagship technology, the Nuro Driver™, is licensed to cater to various applications, including robotaxis, commercial fleets, and personal vehicles. With years of proven self-driving deployments, Nuro provides automakers and mobility platforms a clear pathway to commercial-scale autonomous vehicles, fostering a safer, more connected future. About the Role We are in search of a Senior/Staff Software Engineer to take on a pivotal technical leadership role in Nuro’s Machine Learning (ML) Data engine. You will be positioned at the crucial intersection of Autonomy, Machine Learning, and Infrastructure, serving as an architect for the systems that power our autonomy AI models. In this role, you’ll collaborate with the Autonomy team to implement the technical strategy to convert vast amounts of autonomy data into high-value training signals for decision-making. Your responsibilities will include designing and constructing data products for autonomy researchers, developing queries for rare 'needle-in-a-haystack' scenarios, and automating labeling and data ingestion workflows. You will work closely with Autonomy ML researchers to grasp their data needs, cooperate with infrastructure teams to establish the appropriate data interfaces and APIs, and develop robust tools for data selection, simulation, and introspection, all capable of handling data at scale. If you thrive on solving complex problems with practical solutions that impact the real world, we invite you to join us. About the Work Data Pipeline Architecture: Design and implement scalable data ingestion and processing pipelines that transform data streams into targeted training datasets. Lead efforts to enhance data quality, identify anomalies, and manage out-of-distribution examples to ensure effective model training and deployment. Cross-Functional Leadership: Collaborate with autonomy teams and data infrastructure teams to create effective ML data pipelines and products for ML engineers. ML Tooling & Introspection: Build infrastructure and visualization tools that enable ML researchers to easily introspect data, identify model failure modes, request new data samples, and comprehend shifts in data distribution. Labeling Operations Integration: Work closely with the data operations team to establish quality standards for labeling operations.

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.