Aeva, Inc. is seeking a Machine Learning Engineer with a focus on Perception to join the team in Mountain View, CA. This role centers on developing algorithms that help autonomous systems interpret and respond to their environment. The work draws on both machine learning and computer vision to improve how autonomous vehicles perceive the world around them. Key responsibilities Design and build perception algorithms for autonomous platforms Use machine learning and computer vision on real-world datasets Support progress in autonomous vehicle technology through technical contributions Work closely with engineers and researchers to expand product capabilities Location This position is based in Mountain View, CA.

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

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

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.

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.

Waymo is a pioneering autonomous driving technology company with a vision to become the most trusted driver in the world. Originating from the Google Self-Driving Car Project in 2009, we have dedicated ourselves to developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access while preventing countless lives lost in traffic accidents. The Waymo Driver is the backbone of our fully autonomous ride-hailing service and can be adapted to various vehicle platforms and product use cases. To date, the Waymo Driver has successfully completed over ten million rider-only trips, backed by its extensive experience of autonomously navigating over 100 million miles on public roads and tens of billions of miles in simulation across more than 15 U.S. states.The Perception team is responsible for creating the systems that interpret spatial-temporal representations and their semantic meanings of the environment surrounding the self-driving car. We collaborate closely with downstream teams to optimize and integrate these systems into the Waymo Driver. Our team conducts innovative research to solve real-world challenges and partners with research teams at Alphabet, leveraging millions of miles of driving data from a diverse range of sensors. This enables our engineers to (1) devise methods for continuous learning from large-scale real-world data, (2) design and scale model training, (3) analyze real-world behavior and develop systems for managing real-world complexities, and (4) optimize models for our onboard and offboard hardware.In this hybrid role, you will report to a Senior Staff 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, Waymo has tirelessly worked on developing the Waymo Driver—The World's Most Experienced Driver™—to enhance mobility access and save lives lost to traffic accidents. The Waymo Driver fuels our fully autonomous ride-hailing service and can adapt to various vehicle platforms and applications. With over ten million rider-only trips completed, Waymo has amassed more than 100 million miles driven autonomously on public roads, supplemented by tens of billions of simulated miles across 15+ U.S. states.The Perception team at Waymo is instrumental in crafting the technology that empowers the Waymo Driver. Our advanced models enable the Waymo Driver to interpret its surroundings, make informed decisions, and ensure safe passage for passengers. Engaging in research to tackle real-world challenges, we collaborate closely with Alphabet's research teams. Our access to extensive driving data from diverse sensors allows machine learning practitioners to develop scalable multi-modal models and techniques.You will report directly to our Director of Engineering within the Perception Organization.

Waymo is a leader in autonomous driving technology dedicated to becoming the most trusted driver in the world. Originating from the Google Self-Driving Car Project in 2009, our focus has been on creating the Waymo Driver—an exceptional driver that enhances mobility access while significantly reducing traffic-related fatalities. The Waymo Driver not only supports our fully autonomous ride-hailing service but can also be adapted to various vehicle platforms and applications. With over ten million rider-only trips completed, our technology has safely navigated more than 100 million miles on public roads and processed tens of billions of miles in simulation across over 15 U.S. states.The Perception Data team at Waymo plays a critical role in shaping the strategy and technical direction for all data utilized in training and evaluating the Waymo Driver's perception capabilities. We manage the complete data lifecycle, developing automated systems and 'infrastructure-as-product' solutions that convert vast amounts of driving sensor data into high-quality training datasets. Our team tackles complex challenges, including active learning loops and open-vocabulary modeling, bridging raw data with advanced machine learning techniques.By integrating data ingestion, curation, and evaluation into a unified ecosystem, we facilitate the swift development of foundational models and next-generation perception systems. We work closely with Machine Learning, Infrastructure, and Evaluation teams to address intricate data challenges, ensuring our models can effectively interpret the long-tail of rare events. Ultimately, our contributions lay the groundwork for the Waymo Driver to operate safely in diverse environments.

Waymo is at the forefront of autonomous driving technology, aiming to become the world's most trusted driver. Originating from 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 reduce the tragic loss of life due to traffic accidents. The Waymo Driver powers our fully autonomous ride-hailing service and can be adapted to various vehicle platforms and use cases. With over ten million rider-only trips and extensive experience driving autonomously over 100 million miles on public roadways, complemented by tens of billions of miles in simulations across 15+ U.S. states, we are leading the way in this transformative field.The Perception team is responsible for creating the systems that learn the spatial-temporal representations and semantic meanings of the self-driving car's surroundings, effectively enabling the car to 'perceive' its environment. We collaborate closely with downstream teams to optimize and integrate our findings into the Waymo Driver. Our research tackles real-world challenges, leveraging vast amounts of driving data from diverse sensors. As part of our team, you will work on methods for continuous learning from large-scale real-world data, model development and training at scale, behavioral analysis, and system optimization for both onboard and offboard hardware.In this hybrid role, you will report 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.

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.

Waymo is a pioneering autonomous driving technology firm on a mission to become the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has been dedicated 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 serves as the backbone for our fully autonomous ride-hail service and has the potential to be integrated across various vehicle platforms and applications. With over ten million rider-only trips facilitated by its extensive experience of more than 100 million miles driven autonomously on public roads and tens of billions of miles in simulation across over 15 U.S. states, Waymo is at the forefront of autonomous technology.At Waymo, machine learning models form the essence of our fully autonomous driving capabilities. These models empower the Waymo Driver to interpret its surroundings, make accurate decisions, and transport individuals safely to their destinations. We tackle intricate technical challenges in perception, planning, and control, collaborating closely with hardware and systems engineers. If you are passionate about Level 4 autonomous driving, we would love to connect with you.As an intern at Waymo, you will collaborate with industry leaders on impactful projects that contribute significantly to our mission. We believe in a reciprocal learning experience: you will apply your expertise while gaining opportunities to expand your skill set. Interns are integral to our culture and serve as a vital part of our talent pipeline. Join Waymo for an engaging and fulfilling internship experience!This internship will be conducted on-site at our headquarters in Mountain View, CA.

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.

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.

Waymo, a leader in autonomous driving technology, aims to become the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo is dedicated to creating the Waymo Driver—The World's Most Experienced Driver™—to enhance mobility accessibility while significantly reducing traffic-related fatalities. Our technology powers a fully autonomous ride-hail service and is adaptable across various vehicle platforms and applications. The Waymo Driver has successfully completed over ten million rider-only trips, supported by extensive real-world driving data accumulated over 100 million miles on public roads and tens of billions in simulated environments across more than 15 U.S. states.The Perception team is instrumental in developing the system that interprets the spatial-temporal representation and semantic meanings of the car's surroundings. Our collaboration extends to downstream teams for optimization and integration into the Waymo Driver. Engaging in innovative research, we tackle real-world challenges and partner with research experts at Alphabet. With access to millions of miles of diverse sensor data, our engineers focus on developing scalable learning methods from large-scale real-world data, model training, behavioral analysis, and optimization for both onboard and offboard hardware.In this hybrid position, you will report directly to a Staff Technical Lead Manager.

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, committed to becoming the world's most reliable driver. Originating from 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 significantly reduce the number of lives lost to traffic accidents. The Waymo Driver underpins our fully autonomous ride-hailing service and can be adapted to various vehicle platforms and applications. With over ten million rider-only trips completed, our technology has autonomously navigated more than 100 million miles on public roads and billions in simulation across over 15 U.S. states.The Perception team is responsible for creating systems that learn the spatial-temporal representation and semantic meanings of the self-driving car's environment. Our work involves close collaboration with downstream teams for optimization and integration with the Waymo Driver. We engage in innovative research to tackle real-world challenges while partnering with Alphabet's research teams. With access to extensive driving data from diverse sensors, our engineers are equipped to (1) devise methods for continuous learning from vast real-world datasets, (2) develop scalable models and training processes, (3) analyze real-world behaviors to manage complex interactions, and (4) optimize models for both onboard and offboard hardware.Within the Perception domain, our Sensor Pipelines team addresses a variety of real-world challenges beyond mere object detection, including weather conditions, road surface understanding, visibility, and the identification of exceptional events surrounding the vehicle. These pipelines encompass a wide range of sensing technologies while integrating throughout the Perception stack and collaborating with planning components.In this hybrid role, you will report to a Director and lead a team of engineers dedicated to Perception machine learning pipelines.Your Responsibilities:Oversee large teams of software engineers tackling diverse Perception product challenges through machine learning, focusing on team development and recruitment to foster resilient, high-performing teams.Guide the team in designing top-tier machine learning solutions in partnership with Technical Leads, nurturing an environment of excellence and high achievement.Act as the team's representative within the broader Perception and Onboard group, collaborating with other leaders on staffing and strategic planning. Establish team Objectives and Key Results (OKRs) and formulate actionable plans to achieve them.

Who We AreAt Ema, we are pioneering cutting-edge AI technologies designed to enhance the creativity and productivity of employees across enterprises. Our unique technology enables organizations to entrust Ema, the AI employee, with repetitive tasks, freeing up human talent for more strategic initiatives. Founded by a team of former executives from tech giants such as Google, Coinbase, and Okta, and backed by prestigious investors including Accel Partners and Naspers, we are on the forefront of the AI revolution.Our diverse team, composed of top engineers from leading tech firms like Microsoft Research and Facebook, brings a wealth of knowledge and experience, primarily from renowned institutions such as Stanford and MIT. Operating out of Silicon Valley and Bangalore, India, we embrace a hybrid work model, requiring employees to be in our Mountain View, CA office three days a week.Who You AreWe seek passionate and innovative Machine Learning Engineers who thrive on tackling complex challenges and enjoy working with vast datasets. You have a talent for translating theoretical concepts into practical, scalable solutions, and you are a collaborative team player who excels in autonomous settings. Your enthusiasm for employing machine learning techniques, particularly in Natural Language Processing and Information Retrieval, is matched only by your desire to contribute to a mission-driven, high-growth startup making a significant impact.Your ResponsibilitiesDesign, develop, and deploy machine learning models that drive our NLP, retrieval, ranking, reasoning, dialog, and code-generation systems.Implement state-of-the-art machine learning algorithms, including Transformer-based models and reinforcement learning, to enhance AI system performance.Analyze and process large, complex datasets (structured, semi-structured, and unstructured) to inform model development.Engage throughout the entire machine learning model lifecycle, from problem identification and data exploration to feature engineering and model evaluation.