Senior/Staff Machine Learning Engineer at Waymo | Mountain View, CA

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 accident…

Join Waymo as a Senior Back-End Software Engineer in our Simulation team, where you will play a vital role in building and enhancing our cutting-edge autonomous driving technologies. You will be responsible for designing and implementing robust back-end systems that support our simulation environments, helping to ensure the safety and efficiency of our self-driving vehicles.Your contributions will directly impact the future of transportation and make a difference in how people move through the world.

Waymo is at the forefront of autonomous driving technology, dedicated to becoming the world’s most reliable 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 lost to traffic accidents. The Waymo Driver is the driving force behind our fully autonomous ride-hailing service and is adaptable to various vehicle platforms and use cases. With over ten million rider-only trips completed, we have amassed experience driving autonomously over 100 million miles on public roads and tens of billions in simulation across more than 15 U.S. states.The Simulator Team at Waymo creates advanced simulations of realistic environments for testing and training the Waymo Driver. We leverage cutting-edge machine learning algorithms to assess and improve the Waymo Driver's performance. As our simulation platform evolves, this technical leadership position will oversee the strategy for the entire Simulator software stack, ensuring it scales with emerging simulation technologies and Waymo’s growth. Your responsibilities will encompass low-level optimization through to high-level configuration, all aimed at enhancing resource utilization (CPU/RAM/TPU/GPU). You will spearhead the Simulator Platform's efficiency initiatives and represent the team in broader performance-related projects within Waymo.In this hybrid role, you will report to a Director of Software Engineering.

At MatX, we are committed to pioneering the compute platform for Artificial General Intelligence (AGI). Our team is engaged in creating comprehensive, vertically integrated full-stack solutions ranging from silicon to systems, incorporating both hardware and software to effectively train and execute the largest machine learning workloads necessary for AGI. Our primary programming language is Rust.Key Responsibilities:Design and sustain functional and performance models of our hardware systems.Create tools and infrastructure to enhance the efficiency of correlation, debugging, and testing processes.Collaborate closely with model stakeholders including architecture, verification/validation, compiler, and runtime teams.Engage in architectural decisions and participate in review processes.Explore and implement performance optimization strategies.

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 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 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.

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.

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.

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 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 committed to developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and save countless lives lost in traffic accidents. Our technology powers a fully autonomous ride-hail service and can be adapted to various vehicle platforms and applications. With over ten million rider-only trips and extensive experience driving more than 100 million miles on public roads and tens of billions of simulation miles across 15+ U.S. states, we are at the forefront of this transformative journey.The Simulation ML Infrastructure team is focused on creating scalable AI/ML infrastructure that accelerates the Simulator team in developing state-of-the-art realistic simulations for testing and training the Waymo Driver. To enhance the realism and steerability of these simulations, we leverage large foundation models trained on vast datasets to accurately represent the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists), road systems, traffic control measures, and environmental conditions.We are looking for a seasoned senior individual contributor to spearhead the advancement of sophisticated AI/ML infrastructure for multi-billion parameter foundation models within ML accelerator-friendly simulations. Your expertise in massive model scaling, ML accelerators, and large-scale distributed systems will be essential in designing and scaling our systems.This position reports to an Engineering Manager.Your Responsibilities:Join a top-tier, high-performing research engineering team to push the boundaries of ultra-realistic multi-agent simulations using foundation models.Collaborate closely with the Waymo Realism Modeling team located in London and the Waymo Oxford team to utilize large foundation models for enhancing simulation realism.Operate at the intersection of data engineering, model development, and simulations, making architectural decisions. Take ownership of large, complex systems, and ensure that architectures and designs align with both technical and business objectives.Design and scale extensive distributed systems that encompass the entire ML lifecycle, facilitating planet-scale dataset generation, model training, and evaluation.Work cross-functionally to derive performance and system-level requirements for large ML systems. Convert product and business goals into measurable technical deliverables, ensuring alignment of system components.

Waymo is a pioneering company in autonomous driving technology, dedicated to becoming the world's most reliable driver. Originating as the Google Self-Driving Car Project in 2009, we have concentrated on creating the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access while preventing countless lives lost to traffic incidents. With over ten million rider-only trips completed and having driven autonomously over 100 million miles on public roads as well as tens of billions in simulations across more than 15 U.S. states, the Waymo Driver powers our fully autonomous ride-hail service and is adaptable to various vehicle platforms and applications.The Simulator Team at Waymo is dedicated to constructing sophisticated simulations of realistic environments for the testing and training of the Waymo Driver. You will be a part of a diverse and collaborative group of machine learning (ML) engineers, software engineers, and data scientists. Our goal is to deliver industry-leading simulation solutions by utilizing advanced ML algorithms to assess and enhance the Waymo Driver's performance. We achieve this by accurately modeling the real world, which includes realistic agents (such as vehicles, pedestrians, cyclists, and motorcyclists), roadways, traffic control systems, and weather conditions, complemented by a comprehensive sensor suite including cameras, LiDAR, and radars.To amplify the fidelity, scalability, and controllability of our simulations, we leverage cutting-edge ML technologies, including large language models, foundational world models, and reconstructive methods trained on extensive datasets, alongside traditional rendering techniques.In this hybrid role, you will report directly to a Senior Staff Engineering Manager.

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

Who We Are Nuro is a pioneering self-driving technology company dedicated to making autonomous solutions accessible to everyone. Established in 2016, we are on a mission to construct the most scalable autonomous driver, merging advanced AI with automotive-grade hardware. Our flagship technology, the Nuro Driver™, is licensed to facilitate a variety of applications, from robotaxis and commercial fleets to personal vehicles. With a proven track record in self-driving deployments, Nuro provides automakers and mobility platforms with a clear pathway to commercially viable autonomous vehicles, fostering a future that is safer, more connected, and enriched. About the RoleSimulation plays a crucial role in the development of autonomous technology. Our Simulation team is tasked with creating a powerful simulator that underpins all simulations at Nuro, enabling us to confidently develop and test our self-driving technologies. The team tackles a variety of novel simulation challenges, employing innovative and creative approaches—ranging from synthesizing sensor data and automating scenario generation to optimizing performance and resources. Collaboration with various teams across the company allows us to broaden the horizons of what can be simulated. About the Work Enhance the functionality, performance, and user experience of our simulator. Develop inventive strategies to elevate simulation realism and coverage through synthesis. Design and implement solutions to streamline interactions among complex systems. Engage in diverse projects, from new greenfield initiatives to scaling existing systems. Work closely with autonomy engineers to deepen your understanding of autonomous systems and devise optimal solutions.

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.

The OpportunityAre you passionate about leading innovative projects that harness AI technology to enhance the value of meetings and conversations? Join our dynamic AI team at Otter.ai, where you will collaborate with seasoned scientists and engineers to advance our machine learning capabilities. As a Senior Machine Learning Engineer, you will leverage your robust software engineering expertise to scale and optimize our ML systems, transforming pioneering research into production-ready features that drive our summarization and conversational intelligence offerings.Your ImpactDesign, build, and advance expansive Speech Recognition, Natural Language Processing, and Large Language Model systems that underpin essential product experiences, including chat and speech understanding across millions of interactions.Lead the architecture and development of training, fine-tuning, post-training, and inference methodologies for large-scale language and speech models utilizing PyTorch and/or JAX, making informed trade-offs among quality, latency, cost, and reliability.Enhance model architectures, loss functions, decoding methods, and training strategies for speech and language models, guided by both research insights and practical constraints.Oversee the complete ML system lifecycle, from research prototyping to production deployment, including monitoring, iteration, and ongoing maintenance.Collaborate closely with product and infrastructure teams to translate groundbreaking research into scalable, production-grade systems that yield significant user and business impact.Drive enhancements in model performance, reliability, observability, and operational excellence using real-world conversational data at scale.Establish technical direction and best practices for ML infrastructure, data pipelines, evaluation frameworks, and deployment processes in a cloud environment.Identify and resolve complex challenges in model behavior, data quality, scaling, and system interactions, often preemptively addressing issues before they affect users.Mentor and uplift fellow engineers, shaping team standards, reviewing designs, and fostering a culture of high-quality technical decision-making and execution.Influence applied research and technical strategies by pinpointing promising speech and multimodal modeling techniques, and driving their validation and adoption.

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.

At Waymo, we are at the forefront of autonomous driving technology, striving to become the world’s most trusted driver. Since our inception as 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 potentially saving thousands of lives lost to 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 rides completed, our technology has driven more than 100 million miles on public roads and tens of billions in simulation across 15+ states in the U.S.We are looking for innovative and collaborative individuals to join our Hardware Engineering team, which includes electrical, mechanical, reliability, software, and vehicle engineers. Together, we design, build, and refine the products that serve as the eyes and ears of Waymo's autonomous driving technology, integrating them into our vehicle platforms. If you are curious and talented, we want you on our team!This position follows a hybrid work model, and you will report to the Tech Lead Manager of the Sensor Software Team.

Waymo, a leader in autonomous driving technology, is dedicated to becoming the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, our focus has been on creating the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and prevent traffic-related fatalities. With our Waymo Driver, we have powered a fully autonomous ride-hail service, achieving over ten million rider-only trips and accumulating experience from over 100 million miles driven on public roads and tens of billions of miles in simulation across more than 15 U.S. states.The Waymo AI Foundations team is on a mission to create machine learning solutions that address critical challenges in autonomous driving, aiming to operate Waymo vehicles safely across numerous cities and under various driving conditions. We actively engage in collaborative efforts with other research teams within Alphabet, focusing on areas such as reinforcement learning, learning from demonstrations, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.This role follows a hybrid work schedule and you will report to a Senior Staff Software Engineer.