Director of Machine Learning

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Waymo is a pioneering company in autonomous driving technology, dedicated to becoming the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has been on a mission to develop the Waymo Driver—The World’s Most Experienced Driver™—which aims to enhance mobility access and prevent the thousands of fatalities caused by traffic accidents. The Waymo Driver is the backbone of our fully autonomous ride-hail service and is adaptable to various vehicle platforms and applications. With more than ten million rider-only trips completed, our technology has successfully navigated over 100 million miles on public roads and simulated tens of billions of miles across more than 15 U.S. states.The Perception team is responsible for creating the systems that learn the spatial-temporal representation and semantic meanings of the environment surrounding the autonomous driving vehicle (ADV). Our work involves close collaboration with downstream teams to optimize and integrate these systems into the Waymo Driver. We actively conduct research to solve real-world challenges and partner with research teams at Alphabet. With access to millions of driving data miles collected from a variety of sensors, our engineers have the opportunity to (1) devise methods for continuous learning from large-scale real-world data, (2) build and train models at scale, (3) analyze real-world behavior and develop systems to manage complex interactions with the environment, and (4) refine models for our onboard and offboard hardware.In this hybrid role, you will report to a Technical Lead Manager.

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.

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.

Join our dynamic team at LinkedIn as a Distinguished Software Engineer in Machine Learning. In this pivotal role, you will lead innovative projects that enhance our growth strategies through cutting-edge machine learning techniques. You will collaborate with cross-functional teams to implement advanced algorithms that drive our product offerings and influence key decisions.

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 developed the Waymo Driver—The World's Most Experienced Driver™—to enhance mobility access and drastically reduce traffic-related fatalities. With over ten million rider-only trips and the ability to autonomously navigate more than 100 million miles on public roads, Waymo is transforming transportation across 15+ U.S. states.The Waymo Mapping team aims to create a high-resolution map of the world to facilitate safe autonomous driving. We employ both automated and manual mapping techniques and develop the necessary infrastructure to store, process, and distribute our maps. Our team collaborates with several other departments within Waymo that utilize map data.In this role, you will:Design, train, and deploy machine learning models that automate the creation of Waymo's HD maps, allowing for scalability in the Waymo Driver.Utilize and advance cutting-edge ML techniques, including Vision-Language Models (VLMs) and Generative AI, to innovate in mapping automation.Manage the entire model development lifecycle, from data mining and processing to model training, evaluation, validation, and production.Work closely with partner ML teams, such as Waymo Perception and Waymo AI Foundations, to implement pioneering research into scalable, reliable, production-ready solutions.

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.

Are you driven by a passion for solving complex AI challenges and eager to play a pivotal role in revolutionizing enterprise automation? Join Kognitos as we shape the future of software development!Your Contributions Will Include:Optimizing Resource Utilization: Create cutting-edge strategies to enhance resource efficiency in training and fine-tuning machine learning models, ensuring optimal performance without compromising on resource usage.Developing Intelligent Workflows: Innovate workflows that empower AI to reason, plan, and execute tasks consistently, reducing errors and unexpected outcomes.Integrating Multimodal Language Models: Engage in multimodal projects that blend text, images, and various data formats to develop robust, enterprise-ready automation solutions.Enterprise-Scale AI Solutions: Deliver AI systems that address enterprise needs, targeting a reduction of operational costs by 30% through widespread adoption.Key Responsibilities:Design and implement machine learning models with a focus on intelligent workflows and reliable task execution.Refine AI systems for multimodal applications, effectively tackling real-world challenges faced by enterprises.Pioneer new fine-tuning methodologies to enhance resource utilization and model efficacy.Ensure alignment of AI systems with regulatory standards while delivering consistent business outcomes.Collaborate with diverse teams, including product management, engineering, and business stakeholders, to drive impactful solutions.Stay abreast of the latest advancements in AI research, integrating cutting-edge developments into Kognitos’ platform.Qualifications:A Bachelor's, Master's, or Ph.D. in Computer Science, Machine Learning, or a related discipline.Demonstrated experience in developing and deploying machine learning models in production settings.Expertise in fine-tuning techniques for large-scale models and resource optimization.Strong intuition and experience with Large Language Models (LLMs).Familiarity with multimodal language models and their applications in enterprise environments.

At Waymo, we are pioneering autonomous driving technology, striving to become the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, our mission has been to create the Waymo Driver—The World’s Most Experienced Driver™. This advanced technology aims to enhance mobility access while significantly reducing the number of lives lost in traffic accidents. The Waymo Driver currently powers our fully autonomous ride-hail service and is adaptable across various vehicle platforms and use cases. With over ten million rider-only trips completed, our system has amassed experience from autonomously driving over 100 million miles on public roads and simulating tens of billions of miles across more than 15 U.S. states.The Perception team is responsible for developing the systems that learn the spatial-temporal representations and their semantic meanings within the car's environment. Our collaborative efforts with downstream teams focus on optimizing and integrating these systems into the Waymo Driver. We conduct groundbreaking research to tackle real-world challenges and partner with research teams at Alphabet. Leveraging millions of miles of driving data collected from diverse sensors, our engineers are empowered to (1) develop methodologies for efficient and continuous learning from large-scale real-world data, (2) design and train models at scale, (3) analyze real-world behaviors and build systems to navigate complex real-world interactions, and (4) optimize our models for both onboard and offboard hardware.In this hybrid role, you will report directly to a Senior Staff Technical Lead Manager.

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.

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.

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.

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.

Waymo is at the forefront of autonomous driving technology, striving to become the world’s most reliable driver. Originating from the Google Self-Driving Car Project in 2009, our mission has been to develop the Waymo Driver—the world's most experienced driver—to enhance mobility access and save countless lives lost to traffic accidents. The Waymo Driver powers our fully autonomous ride-hail service and can be adapted to various vehicle platforms and product applications. With over ten million rider-only trips and more than 100 million miles driven autonomously on public roads, along with tens of billions of miles simulated across more than 15 U.S. states, we are redefining transportation.The Perception team is dedicated to building systems that learn the spatial-temporal representations and semantic meanings of the environment around the autonomous driving vehicle (ADV). We collaborate closely with downstream teams to optimize and integrate these systems into the Waymo Driver. Our research tackles real-world challenges and involves collaboration with Alphabet’s research teams. With access to millions of miles of diverse driving data from various sensors, our engineers develop methods for efficient and continuous learning from large-scale real-world data, model training at scale, real-world behavior analysis, and optimizing models for both onboard and offboard hardware.In this hybrid role, you will report to a Technical Lead Manager.

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 empowers a fully autonomous ride-hail service and is adaptable across various vehicle platforms and product applications. With over ten million rider-only trips facilitated by the Waymo Driver and more than 100 million miles driven autonomously on public roads, we are paving the way for safer transportation.The Perception team is responsible for developing systems that interpret the spatial-temporal representations and semantic meanings of the environment surrounding our autonomous vehicles. Our collaborative efforts with downstream teams focus on optimizing and integrating these systems within the Waymo Driver. We engage in innovative research to tackle real-world challenges and work closely with research teams at Alphabet. Our engineers have access to extensive driving data from diverse sensors, allowing us to (1) create efficient learning methods from vast real-world datasets, (2) build and train models at scale, (3) analyze real-world behaviors, and (4) optimize models for both onboard and offboard hardware.In this hybrid role, you will report 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 pioneering the future of autonomous driving with a commitment to being the world’s most trusted driver. Since its inception as the Google Self-Driving Car Project in 2009, Waymo has been dedicated to creating the Waymo Driver—the world's most experienced driver. This innovation aims to enhance mobility access while drastically reducing traffic-related fatalities. The Waymo Driver currently powers our fully autonomous ride-hail services and is adaptable to various vehicle platforms and applications. With over ten million rides provided and an extensive driving experience accumulated over 100 million miles on public roads, plus tens of billions of simulated miles across more than 15 U.S. states, we are setting the standard for safety and reliability in transportation.We are on the lookout for an accomplished Technical Lead Manager (TLM) to guide our Vehicle Understanding team. In this pivotal role, you will oversee the production modules pertinent to Vehicle Understanding for the Waymo Driver. This encompasses the fine-grained classification of vehicles (e.g., emergency, railed, construction, towing), their states (e.g., warning, temporal blockage, active loading/unloading), and their intents (e.g., lane changes, stalled/slow vehicles, double-parking, unparking). As a key player in Waymo's expansion both domestically and internationally, your contributions will have an immediate impact on enhancing the generalizability of the Waymo Driver.In this hybrid position, you will report directly to our Senior Staff TLM of Semantics Understanding.

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.