Senior Machine Learning Engineer - LLM/VLM Distillation

Waymo seeks a Senior Machine Learning Engineer with a focus on Large Language Model (LLM) and Vision-Language Model (VLM) distillation. This role is based in Mountain View, California, and centers on advancing the machine learning models that drive Waymo’s autonomous vehicles. Collaboration with both data science and engineering teams is a key part of the work, with an emphasis on refining and optimizing model performance. Key responsibilities Design and implement algorithms to distill LLMs and VLMs for greater efficiency. Work with large datasets to support learning and adaptation in self-driving systems. Partner with cross-functional teams to bring optimized models into production environments. Continually improve the performance and efficiency of models that power autonomous driving technology. Requirements Hands-on experience with machine learning, with a strong background in LLM and VLM distillation. Proven problem-solving skills and the ability to apply machine learning creatively to practical challenges. Interest in tackling real-world problems related to autonomous vehicles.

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, 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.

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, striving to be the world's most trusted driver. Originating as 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 save countless lives that are lost to traffic accidents. The Waymo Driver powers our fully autonomous ride-hailing service and can be integrated into various vehicle platforms and applications. With over ten million rider-only trips completed and extensive experience gained from autonomously driving over 100 million miles on public roads and tens of billions of miles in simulation across more than 15 states, we are leading the way in transforming transportation.The Waymo Applied Research team is committed to pioneering machine learning solutions that tackle significant challenges in autonomous driving, with the ultimate aim of safely operating Waymo vehicles across numerous cities and diverse driving conditions. Our team actively initiates and nurtures collaborations with other research teams within Alphabet to drive innovation.In this hybrid role, you will report directly to a Technical Lead Manager.

Join Waymo as an Applied Research Scientist focusing on Perception LLM/VLM technologies. In this role, you will contribute to cutting-edge research and the development of advanced algorithms that enhance our self-driving technology.

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, our mission has been to enhance mobility access while significantly reducing traffic-related fatalities. The Waymo Driver, our cutting-edge autonomous technology, powers a fully autonomous ride-hail 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, our system has been tested extensively, further driving our commitment to safety and innovation.The Driver Understanding and Evaluation (DUE) Machine Learning team is tasked with developing and managing scalable machine learning and data systems, enhancing our simulation workflows and analytical tools, and refining the evaluation processes for developer onboarding. This team merges expert human insights with advanced machine learning techniques to provide robust training and evaluation data for the myriad metrics and components that define the Waymo Driver. We seek talented researchers and software engineers who are enthusiastic about pioneering machine learning approaches for our evaluation systems, driving continuous improvements in our technology stack.Key Responsibilities:Develop a comprehensive strategy for next-generation, machine learning-based evaluation metrics while ensuring scientific and statistical rigor across our AI applications.Design and implement scalable systems for training and fine-tuning large-scale generative models to simulate realistic driving behaviors.Lead efforts in creating, implementing, and iterating innovative reinforcement learning (RL) algorithms and reward functions tailored to generate high-fidelity driving behaviors.Oversee the development of advanced Deep Learning models and Generative AI solutions to enhance triaging processes, automate high-volume workflows, and perform nuanced analyses of self-driving behaviors to identify critical anomalies.Stay informed on best practices within Alphabet and the broader industry to develop a state-of-the-art Reinforcement Learning from Human Preference (RLHF) based data collection and evaluation system.Provide mentorship, guidance, and thought leadership to engineers within the team and across collaborative groups.Coordinate and align multiple teams—including Driver Understanding, Simulation, System Engineering, Research, and Onboard Software—to ensure cohesive evaluation methodologies.

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.

What You'll Be DoingJoin Moveworks as a Senior Machine Learning Engineer focused on developing advanced ML infrastructure for deploying and managing Large Language Models (LLMs). This pivotal role involves the design, optimization, and scaling of comprehensive machine learning systems that drive our AI solutions. The ML Infrastructure team is responsible for a range of critical functions, including distributed training and inference pipelines, model evaluation, and latency optimization for LLMs. Our work supports numerous ML and NLP models currently in production, impacting millions of enterprise users. You will tackle real-world challenges related to service scalability and algorithm optimization.Your collaboration with our machine learning team, data infrastructure team, and various cross-functional experts will directly enhance our customers' AI experience. This is an opportunity to play a vital role in the long-term scalability of our core AI product and the success of the company. If you seek a high-impact, fast-paced environment to elevate your career, we want to hear from you!Design, develop, and enhance scalable machine learning infrastructure for training, evaluating, and deploying LLMs.Create abstractions to automate diverse steps in various ML workflows.Collaborate with interdisciplinary teams of engineers, data analysts, machine learning specialists, and product managers to introduce innovative features.Utilize your expertise to promote best practices in machine learning and data 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.

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.

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.

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.

Role Overview Waymo is hiring a Machine Learning Engineer focused on infrastructure for driver understanding and evaluation. This position is based in Mountain View, CA. What You Will Do Work closely with a team to advance autonomous driving systems. Develop and maintain infrastructure that supports machine learning models for vehicle perception and environmental interaction. Apply expertise in building and scaling machine learning solutions that help vehicles interpret and respond to their surroundings. About the Team This group focuses on improving how autonomous vehicles understand and evaluate driver behavior, aiming to make self-driving technology safer and more effective.

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, 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.

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.