Machine Learning Engineer (Infrastructure) - Driver Understanding and Evaluation

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 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.

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.

Be Part of the Future of Home RoboticsAt Sunday Robotics, we are pioneering the development of personal robots that alleviate the burden of repetitive household tasks. Our mission is to democratize access to advanced robotics, allowing families to reclaim precious time.After an intensive 18 months of assembling a talented team, securing funding, and validating our innovative technology, we are eager to welcome passionate individuals to join us as we embark on the next exciting chapter of our journey. If you are enthusiastic about contributing your skills to the cutting edge of robotics, we want to hear from you!The RoleAs a Machine Learning Infrastructure Engineer at Sunday Robotics, you will play a pivotal role in shaping the future of home robotics. You will develop end-to-end machine learning models for robotic manipulation, creating foundational systems that will expedite our efforts to introduce robots into everyday homes.This versatile position can be customized to align with your specific expertise, whether it be in data pipelines, training infrastructure, or inference. Your contributions will span the entire robot learning pipeline: from ingesting and processing multimodal data to scaling distributed training, optimizing real-time inference, and developing research tools.What You Will AccomplishEnhance the research codebase for optimal ergonomics and rapid iteration.Oversee model training infrastructure, including job scheduling, checkpointing, metrics, and logging.Facilitate distributed training across GPU clusters with minimal friction for researchers.Enable the training of larger models through techniques such as sharding and memory optimization.Profile and enhance GPU utilization, memory efficiency, and training throughput.Create low-latency inference pipelines for real-time robot control, employing techniques to optimize performance.Collaborate closely with researchers and roboticists to transform research requirements into robust software and infrastructure.Data Pipelines and Research ToolsArchitect high-throughput pipelines for the ingestion, validation, and transformation of multimodal robot data such as video and proprioception.Develop efficient storage systems and metadata indexing for seamless data retrieval.

About NewsBreakEstablished in 2015, NewsBreak is a pioneering Content Intelligence platform redefining the content economy. With a robust user base of over 40 million monthly active users, our flagship platform delivers tailored local news and information, powered by cutting-edge AI, recommendation systems, and advanced adtech.Acknowledged by Fast Company as #32 among the Top Workplaces for Innovators, we proudly hold Great Place to Work® certification and foster a vibrant team of technologists, product innovators, and business leaders dedicated to addressing significant challenges at scale.Achieving unicorn status in 2021, we remain steadfast in our commitment to high growth, seeking the ideal team to realize our mission: to establish the foundational infrastructure for content intelligence.If you’re driven to dream big, innovate rapidly, and make a meaningful impact, we want to hear from you! For more details, visit www.newsbreak.com/aboutAbout the Role:We are seeking a Machine Learning Infrastructure Engineer to join us in building the pivotal infrastructure that trains, serves, and monitors the models behind our Ads and Recommendations products. You will be part of a small, high-responsibility team that implements platform enhancements end-to-end—collaborating with product and data teams to minimize latency and costs while expediting the transition from concept to safely launched model.Your role will encompass the entire ML lifecycle: enhancing training efficiency and reliability, optimizing model serving performance, and fortifying our feature/embedding platform to ensure models remain current and consistent across offline and online applications. We are looking for someone who takes genuine ownership, completes tasks, and elevates the standards for stability and developer experience.Why This Role:Scope & Impact: Join a small team with a significant influence—your contributions will directly impact production.Ownership: Manage everything from design to rollout and post-launch insights; enjoy real autonomy with support.Growth: Gain visibility across the stack and a clear pathway to lead projects and mentor others.Pragmatic Culture: We prioritize outcomes over jargon, valuing clear thinking and follow-through.

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.

The Role Join Moveworks as a Senior Machine Learning Engineer II, where you will play a pivotal role in enhancing our Natural Language Understanding (NLU) and Agentic AI capabilities. Your expertise in software engineering and machine learning will help create seamless user experiences and optimize our generative and conversational AI platform. As part of the NLU team, you will leverage cutting-edge tools in Natural Language Processing (NLP) and Natural Language Generation (NLG), including advanced Large Language Models (LLMs), multimodal foundation models, and hybrid vector databases. You'll have all the necessary infrastructure at your fingertips to fine-tune, evaluate, and deploy your models into production. Our data-centric approach is supported by a world-class annotation team that ensures the creation of high-quality, privacy-conscious datasets for model training and evaluation. Your mission will extend beyond mere model training; you will strive for exceptional AI performance across all metrics, including accuracy, latency, reliability, and the overall functionality of user-facing systems. Our ideal candidates are driven not only by the desire to develop high-performing models but also by the ambition to design and enhance comprehensive AI systems and their components. We are focused on accelerating our operations, tackling complex engineering challenges, and maximizing the value we deliver to our customers. Your contributions will be crucial in achieving our objectives of resolving enterprise issues and establishing the most dependable AI co-pilot ever seen, in collaboration with various teams at Moveworks.

Join the Coupang team as a Senior Staff Machine Learning Infrastructure Engineer focusing on Search & Discovery. In this pivotal role, you will drive the development and optimization of our machine learning infrastructure, ensuring our systems can meet the demands of millions of users.We are looking for experts who are passionate about leveraging cutting-edge technology to deliver exceptional user experiences. Your contributions will directly impact how our customers interact with our platform, making shopping, eating, and living easier than ever.

Unity Technologies is building an offline machine learning platform to support analytics, experimentation, attribution, and AI-driven decisions across the organization. This platform processes both batch and streaming data at scale, serving as the backbone for product intelligence, machine learning pipelines, and business operations. As data sets grow in size and complexity, the platform enables advanced model training, feature generation, and experimentation workflows that are critical for production ML systems. What you will do Design and enhance Unity's offline machine learning infrastructure to support large-scale needs Develop reliable systems for generating training datasets and managing machine learning workflows Support efficient, distributed model training across teams Collaborate with machine learning engineers and platform teams to ensure pipelines scale with data growth and evolving training requirements Shape processes for dataset preparation, model training, validation, and delivery to distributed systems Maintain high standards for reliability, scalability, and performance of the offline ML platform Requirements This role requires a senior technical leader with experience in large-scale machine learning infrastructure. A successful candidate has a strong background in building and maintaining reliable, scalable, and well-architected ML pipelines. Location This position is based in Mountain View, CA, USA.

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 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 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.

Join Our Mission at NuroNuro is pioneering the realm of self-driving technology with a vision to make autonomy accessible to everyone. Established in 2016, we are engineering the world’s most scalable driving solution by merging advanced AI with resilient automotive-grade hardware. Our flagship technology, the Nuro Driver™, is licensed for a variety of applications, from robotaxis to commercial fleets and private vehicles. With years of successful deployments, Nuro offers automakers and mobility platforms a streamlined pathway to commercial-scale autonomous vehicles, cultivating a safer, more integrated future.Role OverviewNuro is in search of a seasoned Technical Lead Manager with robust experience in large-scale infrastructure and workload orchestration, along with proficiency in batch and streaming data processing systems, to enhance our ML Infrastructure team. In this pivotal role, you will spearhead the development of our core platform, guaranteeing our researchers and engineers have uninterrupted access to the compute and data resources vital for advancing autonomous driving technology.As a Technical Lead Manager, you will define the strategy for automated resource provisioning, high-performance workload scheduling, and efficient feature management. You will strike a balance between hands-on technical leadership and effective people management, guiding a talented team while collaborating closely with ML Research and Autonomy teams to remove infrastructure bottlenecks and expedite the Nuro Driver™ development process.Key ResponsibilitiesAs the Technical Lead Manager for ML Platform Infrastructure, you will construct the backbone that fuels Nuro’s model development journey from experimentation to production, including:Technical Strategy Development: Crafting a roadmap for a cohesive ML platform that simplifies complex cloud infrastructure.Resource Provisioning & IaC: Expanding our automated infrastructure-as-code (IaC) pipelines to oversee thousands of GPU/CPU nodes across multiple environments.Intelligent Scheduling: Engineering and fine-tuning workload orchestration to optimize hardware use, minimize job wait times, and manage extensive distributed training.Data Processing & ETL: Creating robust pipelines for the extraction and transformation of petabyte-scale sensor and telemetry data into machine learning-ready formats.Feature Management: Implementing effective feature caching and storage solutions to diminish redundant computations and guarantee quick access to pre-computed features.Team Leadership: Fostering a high-performance culture while mentoring team members.

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 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.

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.

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, dedicated to becoming the world’s most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has been relentlessly focused on creating the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and prevent traffic-related fatalities. The Waymo Driver is the driving force behind our fully autonomous ride-hail service, optimized for various vehicle platforms and applications. With over ten million rider-only trips and more than 100 million miles driven autonomously on public roads, alongside tens of billions of simulated miles across 15+ U.S. states, Waymo is redefining transportation.The ML Platform team at Waymo plays a critical role by offering a suite of tools that facilitate and automate the entire machine learning workflow lifecycle, including feature and experiment management, model development, optimization, and monitoring. Our initiatives have made machine learning more accessible across diverse teams at Waymo, including Perception, Planner, Research, and Simulation.We are seeking talented engineers with expertise in machine learning software or systems to enhance compute performance both in the cloud and on vehicles. You'll engage with the entire ML stack from a systems perspective, tackling challenges such as efficient deep learning models, model compression, and improving ML software (e.g., JAX, XLA, Triton, and CUDA). This hybrid position reports directly to the Senior Manager of Runtime and Optimization.

Join Coupang as the Director of Machine Learning Engineering and lead transformative projects that will redefine customer experiences. You will spearhead our machine learning initiatives, collaborating with cross-functional teams to drive innovative solutions across our e-commerce platform.Responsibilities include:Developing and implementing cutting-edge machine learning algorithms.Leading a team of data scientists and engineers.Collaborating with stakeholders to identify opportunities for leveraging data to enhance customer satisfaction.To apply, please complete the Internal Transfer Request Form using your Coupang email address.

Be a Part of the Future of Home RoboticsAt sunday, we are pioneering the development of personal robots designed to liberate individuals from the burden of repetitive tasks. Our mission is to democratize access to generalized robotics, allowing families to reclaim precious time spent on mundane activities.After investing 18 months in assembling an exceptional team, securing investment, and validating our technology, we are on the lookout for passionate professionals eager to join us during this exciting phase of growth. If you are ready to channel your expertise into cutting-edge robotics innovation, we want to hear from you.Your RoleAs a Full Stack Engineer focused on ML Data & Evals, you will serve as the vital link between raw data and robotic intelligence. You’ll create the foundational infrastructure for our ML team to evaluate and deploy models effectively. Your contributions will expedite the research-to-production cycle, facilitating on-robot evaluations and visualizing model performance in intricate, real-world settings.Key ResponsibilitiesDesign Interactive Data Systems: Develop interfaces and engines that integrate robot and Skill Capture Gloves™ data, enabling efficient human-in-the-loop workflows, from episode annotation to seamless transitions between autonomous operation and manual teleoperation.Conduct Evaluations & Benchmarking: Create high-performance tools to compare model-driven motions with human-captured ground truths, aiding in the assessment of model advancements across various tasks.Data Processing & Orchestration: Design processing services that convert raw captures and sensor data into formats suitable for machine learning, ensuring a smooth transition from our global data collection systems to the models that power our robots.Adaptability in a Startup Environment: While your primary focus will be the ML Platform, our Full Stack Engineers should be versatile, readily adjusting to shifting priorities and contributing across different areas of the stack as we grow.