Machine Learning Engineer - Model Optimization

Waymo is at the forefront of autonomous driving technology, dedicated to becoming the world's most trusted driver. Established in 2009 as the Google Self-Driving Car Project, Waymo has developed the Waymo Driver—The World’s Most Experienced Driver™—aimed at enhancing mobility access and saving countless lives from traffic-related accidents. Our technology em…

Waymo, an innovator in autonomous driving technology, is dedicated to becoming the world's most reliable driver. Originating as the Google Self-Driving Car Project in 2009, our focus has been on creating the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and prevent traffic-related fatalities. The Waymo Driver supports our fully autonomous ride-hail service and can be integrated into various vehicle platforms for diverse applications. With over ten million rides provided and experience from driving more than 100 million miles on public roads combined with billions of miles in simulation across 15+ U.S. states, we’re at the forefront of a transportation revolution.The Perception team is responsible for developing systems that learn spatial-temporal representations and their semantic meanings within the autonomous vehicle's environment. Collaborating closely with other teams for optimization and integration into the Waymo Driver, we engage in research to tackle practical challenges and work with Alphabet's research teams. With access to millions of miles of diverse driving data, our engineers can (1) create methods for efficient and continuous learning from large-scale real-world data, (2) build and train models at scale, (3) analyze real-world behavior to manage complex interactions, and (4) optimize models for our onboard and offboard hardware.In this hybrid role, you will report directly to a Technical Lead Manager.

Waymo is an innovative leader in autonomous driving technology, dedicated to transforming mobility and enhancing safety on the roads. Originating from the Google Self-Driving Car Project in 2009, our mission is to develop the Waymo Driver—The World’s Most Experienced Driver™—to significantly reduce traffic-related fatalities and improve accessibility to transportation. The Waymo Driver is the backbone of our fully autonomous ride-hailing service and is adaptable across various vehicle platforms and use cases. To date, we have successfully completed over ten million trips and have driven autonomously for more than 100 million miles on public roads along with extensive simulation miles.The Waymo AI Foundations team is at the forefront of advancing machine learning solutions to tackle critical challenges in autonomous driving. Our objective is to ensure the safe operation of Waymo vehicles in diverse urban environments and under varying driving conditions. We actively collaborate with other research teams within Alphabet to drive innovation in areas such as reinforcement learning, generative modeling, and robust evaluation.This position offers a hybrid work schedule, and you will report directly to a Senior Staff Software Engineer.

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, striving to become the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo is dedicated to advancing the Waymo Driver—The World's Most Experienced Driver™—to enhance mobility and save lives that are often lost to traffic accidents. The Waymo Driver not only powers our fully autonomous ride-hail service but is also adaptable across various vehicle platforms and use cases. With over ten million rider-only trips completed, our technology has driven autonomously for more than 100 million miles on public roads, supported by tens of billions of miles in simulation across 15+ U.S. states.Our Compute Team plays a pivotal role in delivering the compute platform that runs the software stack of fully autonomous vehicles. We specialize in designing high-performance custom silicon, developing cutting-edge system-level compute architectures that maximize performance, power efficiency, and minimize latency. Our multidisciplinary team thrives on collaboration, working closely with various engineering teams to ensure both hardware and software are optimized for peak performance. We are looking for passionate and talented individuals to join us in developing one of the highest-performing automotive compute platforms in the world.In this hybrid role, you will report to a Hardware Engineering Manager.

About the Role Waymo is looking for a Senior Machine Learning Engineer focused on Prediction & Planning to join the System Architecture team. This position is based in Mountain View, CA, San Francisco, CA, or New York City, NY. What You Will Do Design and implement advanced machine learning algorithms for autonomous vehicle prediction and planning. Develop systems that improve the safety and efficiency of self-driving technology. Collaborate with engineers and researchers across teams to advance core capabilities in autonomous driving. Impact Your work will help shape the systems that guide Waymo’s vehicles, supporting safer and more reliable autonomous transportation.

Moveworks seeks a Senior Machine Learning Engineer to advance the GAI search relevance system. This position is based in Mountain View and centers on improving how users find information on the platform. Key Responsibilities Partner with fellow engineers to design and implement solutions that raise the quality of search results. Work on projects aimed at making the user experience smoother and supporting operational goals. Collaboration and Influence This role involves working alongside engineers who prioritize careful problem-solving and practical improvements. The work directly shapes how users engage with Moveworks’ technology.

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, an innovative leader in autonomous driving technology, is on a mission to redefine mobility by creating the world's most trusted driver. Originating as the Google Self-Driving Car Project in 2009, Waymo has been dedicated to developing the Waymo Driver—The World's Most Experienced Driver™—aimed at enhancing mobility access and preventing traffic-related fatalities. Our autonomous ride-hail service, powered by the Waymo Driver, has completed over ten million trips, with an impressive track record of driving more than 100 million miles on public roads and tens of billions in simulations across 15+ U.S. states.The Perception team plays a crucial role in this journey by constructing systems that learn and interpret the spatial-temporal representations and semantic meanings of the environments surrounding our self-driving vehicles. We collaborate closely with other teams to optimize and integrate these systems into the Waymo Driver, while also conducting cutting-edge research to tackle real-world challenges. Our engineers leverage vast datasets from diverse sensors, allowing them to (1) devise methods for continuously learning from large-scale real-world data, (2) create scalable models and training processes, (3) analyze real-world behaviors to navigate complex interactions, and (4) optimize models for both onboard and offboard hardware.In this hybrid role, you will report to a Technical Lead Manager within the Semantics subgroup of our Perception organization.

Join Moveworks as a Senior Machine Learning Engineer and become a pivotal part of our innovative team dedicated to transforming customer experiences through advanced AI solutions. In this role, you will leverage your expertise in machine learning to develop and implement cutting-edge algorithms that drive our AI systems forward. Collaborate with cross-functional teams to understand user needs and enhance our product offerings.

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 a pioneering company in the autonomous driving sector, dedicated to becoming the world’s most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has been committed to developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and prevent traffic-related fatalities. With over ten million rider-only trips and more than 100 million miles driven autonomously across various U.S. states, Waymo continues to push the boundaries of what is possible in vehicular automation. Our DUE Machine Learning team is tasked with constructing and managing scalable machine learning and data systems, simulation workflows, and insight tools, all aimed at optimizing the evaluation and onboarding processes for developers. This team integrates human expertise with cutting-edge machine learning models to produce training and evaluation data across a multitude of metrics, enhancing the performance of the Waymo Driver. We seek passionate researchers and software engineers excited about advancing machine learning methodologies for our autonomous vehicle evaluation systems, dedicated to enhancing our technology stack's efficacy.

OverviewJoin our innovative team as a Senior Applied AI Engineer, where you will spearhead the development and deployment of transformative applications utilizing Google's generative AI models. This position emphasizes the swift creation of new features and collaboration with partner teams to deliver impactful solutions for Google and esteemed clients. You will play a pivotal role in converting groundbreaking AI research into practical products, showcasing the capabilities of state-of-the-art models. We are in search of engineers with a proven history of developing and launching AI-driven software, ideally within dynamic environments where they have successfully scaled products from concept to production. The perfect candidate will be driven by the chance to influence product and business success.About Google DeepMindAt Google DeepMind, we believe that Artificial Intelligence is one of humanity's most promising inventions. Our diverse team of scientists, engineers, and machine learning specialists is dedicated to pushing the boundaries of AI to create technologies that benefit the public and foster scientific discovery. We prioritize safety and ethics in our work, collaborating with others to tackle significant challenges.The RoleThis position requires a robust foundation in machine learning and a passion for developing and refining software products. We are seeking machine learning engineers who excel in fast-paced settings and possess a demonstrated ability to produce high-quality code. Experience in prototyping, building, and scaling software solutions is essential, particularly in early-stage or startup environments where engineers take ownership of product development from inception to delivery.Key ResponsibilitiesUtilize cutting-edge models to drive impactful real-world outcomes.Develop evaluations, training data, and infrastructure to support AI deployments and quick iterations.Collaborate with researchers and product managers to transform research advancements into concrete product features.Contribute to establishing best practices for building and deploying generative AI applications.Provide insights to influence the development of frontier models.Lead the architecture and development of innovative products and features from concept to launch.About YouTo excel as a Senior Applied AI Engineer at Google DeepMind, we are looking for candidates with the following skills and experience:

Join Moveworks as a Machine Learning Engineering Manager, leading our team dedicated to enhancing search relevance through cutting-edge AI technologies. In this pivotal role, you will oversee the development and deployment of machine learning models that drive our innovative search solutions. Collaborating closely with cross-functional teams, you will ensure the implementation of best practices in machine learning and contribute to the strategic direction of our AI initiatives.

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.

As the Engineering Manager for the Machine Learning Infrastructure team, you will lead the charge in developing a state-of-the-art platform that underpins Moveworks' conversational AI capabilities. This pivotal role is essential for the long-term scalability of our flagship AI product and the overall success of the company.Your primary responsibility will be to oversee a team of skilled engineers dedicated to constructing, optimizing, and expanding the comprehensive systems that facilitate the entire ML/LLM lifecycle. This encompasses our infrastructure for distributed training and inference, model evaluation frameworks, and LLM latency optimization. You will shape the technical direction of the team, harmonizing the operational requirements of our core ML infrastructure with innovative research to create the next generation of LLMs utilizing advanced generative AI.The frameworks your team creates will form the backbone for all ML models deployed in production, serving hundreds of millions of enterprise employees. Your efforts will significantly influence the evolution of the Moveworks Enterprise Copilot platform and the trajectory of AI-driven employee services.

Waymo is a pioneering autonomous driving technology company dedicated to becoming the world’s most reliable driver. Originating from the Google Self-Driving Car Project in 2009, we have concentrated on developing the Waymo Driver—The World’s Most Experienced Driver™—which aims to enhance mobility access and prevent traffic-related fatalities. The Waymo Driver supports Waymo’s fully autonomous ride-hailing service and is adaptable across various vehicle platforms and product applications. Having completed over ten million rider-only trips, our technology has autonomously driven over 100 million miles on public roads and tens of billions in simulations across more than 15 U.S. states.Our Semantics team is committed to producing the highest-fidelity and most comprehensive offboard perception autolabels at scale, serving as the cornerstone for training and validating our autonomous vehicle stack. We are an advanced ML and engineering team utilizing cutting-edge computer vision, deep learning, and generative AI technologies to automatically analyze driving logs, generate detailed scene understanding, and fuel the data engine that allows Waymo to scale safely and efficiently.In this hybrid role, you will report directly to a Technical Lead Manager.Your Responsibilities Will Include:Developing and training state-of-the-art computer vision and multimodal models (e.g., Gemini) to extract rich semantic information such as object attributes and scene properties essential for the AI agent.Designing and implementing a scalable AI agent framework that integrates large foundation models (e.g., Gemini) with outputs from our perception models and internal knowledge bases.Utilizing Fine-tuning and Reinforcement Learning (RL) techniques to establish a 'data flywheel' that continually enhances the system’s captioning and reasoning capabilities through automated feedback.Creating and prototyping innovative prompting strategies for Vision-Language Models (VLMs) to elicit complex causal reasoning related to driving scenarios.Collaborating closely with the ML Infrastructure, Perception, Behavior, and AI Foundation teams to define data requirements and integrate the captioning system into the broader ML development lifecycle.Taking ownership of the entire system lifecycle, from advanced model development and prototyping to production deployment and scaling for massive data generation.

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.

About UsAt MAI (pronounced “my”), we are committed to revolutionizing advanced advertising technology. Our goal is to make state-of-the-art marketing tools, which were previously the domain of large corporations with extensive budgets, available to all businesses. Our innovative platform employs AI agents to streamline and enhance performance marketing, enabling small to medium-sized enterprises to grow their advertising budgets sustainably without the need for agencies or cumbersome manual campaign management.Founded by experienced professionals from leading ad platforms like Google and Instacart, we have successfully secured $25 million in Seed funding led by Kleiner Perkins to accelerate our growth trajectory. This funding will be directed towards expanding our product and engineering teams, fulfilling our vision of intelligent and autonomous marketing. Our AI agents have already demonstrated their effectiveness, assisting clients in achieving 40% more sales while managing millions in monthly Google Ads expenditures. The demand for our services is growing, as evidenced by our rapidly expanding client waitlist.Why Join Us NowAs pioneers in this new frontier of autonomous, intelligent agents, we are charting our own course, and we invite you to be a part of it.As a Machine Learning Engineer at MAI, you will not merely be writing code; you will be a key architect in creating the ecosystem where our AI agents thrive, learn, and perform. Your contributions will significantly impact our entire technology stack—from the foundational data platforms that supply our agents to the core frameworks that enable intelligent reasoning, to the scalable systems that deliver their insights to our clients. This role presents an exceptional opportunity to develop a truly AI-driven product from the ground up and tackle challenges at the forefront of the industry.You will be part of a small, agile team of fewer than ten engineers, allowing you to make a substantial impact and influence the future direction of our company. We are in the early stages of establishing three core teams:Product Engineering & InfrastructureAI Platform & FoundationAgent Application & QualityYou will have the unique opportunity to develop your skills as these teams grow, leveraging your expertise while also embracing new challenges and learning from your peers to become a more well-rounded engineer.

About UsNuro is at the forefront of self-driving technology, dedicated to making autonomy available to everyone. Established in 2016, we are developing the world's most scalable driver by merging innovative AI with robust automotive hardware. Our flagship technology, the Nuro Driver™, is licensed to facilitate a variety of applications, from robotaxis to commercial fleets and personal vehicles. With years of successful self-driving deployments, Nuro is paving the way for automakers and mobility platforms to achieve commercial-scale autonomy, enabling a safer, more interconnected future.Role OverviewOur Sensor Data and Calibration team is expanding, and we are seeking a Senior Software Engineer with a strong background in robotics and machine learning. You will be responsible for designing both online and offline unstructured (targetless) sensor calibration algorithms. The ideal candidate will have extensive hands-on experience in the research, development, and application of machine learning methods utilizing various sensor data types (IMU, camera, lidar, radar, etc.). Familiarity with classical state estimation techniques, such as non-linear least-squares optimization and Lie algebra, is a plus.Key ResponsibilitiesDevelop cutting-edge state estimation and calibration algorithms leveraging both traditional robotics and modern machine learning techniques.Evaluate and characterize the accuracy and performance metrics of state estimation and calibration algorithms.Integrate calibration pipelines into the autonomy system while monitoring onboard performance and resource usage.Collaborate with cross-functional teams to enhance ML model training and overall performance assessment.Address critical inquiries regarding sensor data and overall autonomy effectiveness.