Senior Machine Learning Engineer II - Large Language Models

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, 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 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.

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 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.

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.

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 been committed to developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and save lives lost to traffic accidents. The Waymo Driver not only powers our fully autonomous ride-hailing service but can also be adapted to various vehicle platforms and applications. With over ten million rider-only trips under its belt, the Waymo Driver has driven autonomously over 100 million miles on public roads and completed tens of billions of miles in simulation across more than 15 U.S. states.The Planner Evaluation team tackles one of the primary challenges in autonomous driving: assessing and elevating the quality of the software steering the car. We seek data-driven software engineers and data scientists who are passionate about autonomous vehicles and adept at utilizing complex data to inform decision-making. If this excites you, we encourage you to apply!This position follows a hybrid work model and reports to an Engineering Manager.

Join Waymo, a pioneer in autonomous driving technology, dedicated to becoming the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, our mission is to enhance mobility access and eliminate traffic-related fatalities. The Waymo Driver has already facilitated over ten million rides, showcasing its capability after autonomously navigating over 100 million miles on public roads and trillions in simulations across more than 15 U.S. states.As part of the Release Evaluation team, you will play a key role in ensuring the safety of each Waymo Driver version prior to deployment. We develop automated systems to address rare and exceptional scenarios in autonomous driving, effectively identifying critical signals under constraints of time and resources. The Sampling and Efficiency team utilizes advanced importance sampling techniques and machine learning to enhance the statistical efficiency of our evaluation pipelines.

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 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.

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.

Role Overview Waymo is hiring a Senior Machine Learning Engineer for its Infrastructure team in Mountain View, CA. This position centers on advancing Driver Understanding and Evaluation systems that support autonomous driving technology. What You Will Do Develop and refine machine learning algorithms to boost the accuracy and efficiency of Waymo's self-driving systems. Work closely with engineers and specialists across teams to design and implement technical solutions for Driver Understanding and Evaluation. Contribute to infrastructure that supports large-scale machine learning in the automotive domain. Collaboration This role involves regular collaboration with cross-functional groups, bringing together expertise from multiple disciplines to improve AI-driven vehicle performance.

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.

Join Our TeamAt Unity, we are creating an exceptional ad-tech ecosystem that connects billions of users with the games and experiences they cherish. The Advertiser Growth team plays a pivotal role in this mission, managing the online ads delivery stack, which includes auction, pacing, and bidding systems. As a Senior Machine Learning Engineer, you will significantly contribute to modernizing our core infrastructure and developing backend systems for next-generation AI agents that transform the campaign experience. This position provides an exciting opportunity to tackle complex system challenges at a massive scale while directly impacting Unity’s revenue growth.

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.

About Us Nuro is a pioneering self-driving technology company committed to making autonomy accessible for everyone. Established in 2016, we are developing the world’s most scalable autonomous vehicle, integrating advanced AI with automotive-grade hardware. Our flagship technology, the Nuro Driver™, is licensed to enable a variety of applications, including robotaxis, commercial fleets, and personal vehicles. With a proven track record in self-driving deployments, Nuro provides automakers and mobility platforms a clear pathway to large-scale autonomous vehicles, paving the way for a safer, more connected future. Position OverviewOur robotics division is expanding, and we are on the lookout for an experienced Software Engineer to join our Sensor Data and Calibration team. We seek a candidate with a strong background in robotics and machine learning to create synthetic sensor simulation models and algorithms. The ideal applicant will possess hands-on experience with research, development, and implementation of machine learning techniques (such as NeRF or Gaussian splatting) aimed at generating synthetic sensor data, including photorealistic images and realistic lidar and/or radar outputs. Your Responsibilities Research, develop, and implement cutting-edge synthetic sensor simulation methodologies. Evaluate and characterize the authenticity and utility of synthetic sensor data. Address critical inquiries regarding sensor data and the performance of autonomous systems. Collaborate with cross-functional teams to establish mapping needs and specifications. Candidate Profile One of the following qualifications: PhD in machine learning, computer science, electrical engineering, robotics, or a related discipline with at least 3 years of industry experience. Master's degree with a minimum of 4 years of industry experience. 5+ years of relevant industry experience. In-depth understanding of machine learning principles, with practical experience in training and evaluating modern ML models. Proficient in Python, with familiarity in deep learning frameworks like PyTorch, TensorFlow, or Jax. Desired Skills Comprehensive knowledge of 3D geometry and state estimation concepts. Strong programming skills in systems coding. Experience in simulating/modeling real sensors (camera, lidar, radar, IMU, etc.), including noise modeling. Familiarity with contemporary ML graphics techniques, such as NeRF, Gaussian Splatting, and/or generative models.

About the RoleJoin our dynamic team of experts where machine learning and systems engineering intersect to enhance the performance of autonomous systems. As a Senior Software Engineer specializing in Perception Machine Learning Data, you will play a crucial role in integrating machine learning advancements with autonomy infrastructure, ensuring that our models are trained using the most pertinent, diverse, and high-quality datasets. Your contributions will significantly influence how autonomous systems recognize uncommon scenarios, adapt to various geographical contexts, and operate safely at scale.Key Responsibilities Include:Utilizing Vision Language Models (VLMs) to compile diverse datasets that reflect real-world driving patterns across different regions.Creating high-fidelity synthetic data frameworks across multiple sensor modalities.Enhancing machine learning-powered validation processes for data quality and model preparedness.Your Impact:High-Output Generalist: Collaborate across various domains including autonomy, infrastructure, databases, simulation, and machine learning development, while expanding your expertise in Robotics and ML.Robotics Specialist: Develop cutting-edge solutions for data discovery, automated labeling, and synthetic data generation in close cooperation with the Infrastructure and Autonomy teams.About the WorkTackle the most demanding data challenges in autonomy by applying machine learning and rigorous systems engineering principles:Design hybrid systems that combine deep learning with traditional algorithms for scalable data curation and annotation.Create frameworks to evaluate the real-world authenticity of synthetic data and enhance the quality of synthetic data rendering.Develop tools to automatically identify data gaps that affect the performance of perception models.Collaborate with autonomy engineers to transform raw sensor data into prioritized training objectives, addressing critical gaps that hinder perception and autonomy performance.About YouBachelor’s degree in Computer Science, Robotics, Statistics, Physics, Mathematics, or a related quantitative field.Experience:4+ years of professional software engineering experience, proficient in Python and familiar with C/C++. Demonstrated ability to lead cross-functional technical projects from conception to execution.You have hands-on experience in implementing machine learning solutions and enjoy embedding them into practical systems. Your focus is on delivering impactful, integrated solutions rather than solely theoretical ML projects.Bonus PointsExperience working with synthetic or autonomous driving data.Background in building machine learning systems for robotic applications.