Machine Learning Engineer - Mapping

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 initiated in 2009, our focus has been on developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access while significantly reducing traffic-related fatalities. The Waymo Driver 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 technology has driven more than 100 million miles on public roads and simulated billions of miles across 15+ U.S. states.The Perception team is responsible for building systems that learn spatial-temporal representations and their semantic meanings in the environment surrounding an autonomously driving vehicle (ADV). We collaborate closely with downstream teams to optimize and integrate these systems into the Waymo Driver. Our research addresses real-world challenges, leveraging access to extensive driving data from diverse sensors. This empowers our engineers to develop efficient methods for continuous learning from large-scale real-world data, create scalable models, analyze real-world behaviors, and optimize systems for our onboard and offboard hardware.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 from the Google Self-Driving Car Project in 2009, Waymo has developed the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access while significantly reducing traffic-related fatalities. The Waymo Driver powers our fully autonomous ride-hail service and is adaptable for various vehicle platforms and applications. With over ten million successful rider-only trips and more than 100 million miles driven autonomously on public roads, complemented by tens of billions of miles in simulation across 15+ U.S. states, we are transforming the future of transportation.The Perception team is pivotal in developing the system that learns spatial-temporal representations and their semantic meanings in the environment surrounding our autonomous driving vehicles (ADVs). We collaborate closely with downstream teams for optimization and integration into the Waymo Driver and conduct our own research to tackle real-world challenges. Access to extensive driving data from a variety of sensors enables our engineers to (1) create methods for continuous learning from large-scale real-world data, (2) develop scalable models and model training strategies, (3) analyze real-world behaviors and create systems to handle complex real-world interactions, and (4) optimize models for both onboard and offboard hardware.In this hybrid role, you will report to a Technical Lead Manager.

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.

Waymo is at the forefront of autonomous driving technology, committed to becoming the world's most trusted driver. Originating as the Google Self-Driving Car Project in 2009, our focus has been on developing the Waymo Driver—The World’s Most Experienced Driver™. Our mission is to enhance mobility access while significantly reducing traffic-related fatalities. The Waymo Driver powers our fully autonomous ride-hail service and is adaptable to various vehicle platforms and use cases. With over ten million rider-only trips facilitated, our technology has driven 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 responsible for designing systems that learn spatial-temporal representations and their semantic meanings within the self-driving car's environment. We collaborate with downstream teams for optimization and integration into the Waymo Driver. Our research addresses real-world challenges while working alongside Alphabet's research teams. By utilizing millions of miles of driving data from diverse sensors, engineers are empowered to (1) create efficient learning methods from large-scale real-world data, (2) develop scalable models and training processes, (3) analyze real-world behaviors to manage the complexities of real-world interactions, and (4) optimize models for both our onboard and offboard hardware.In this hybrid role, you will report directly to a Senior Staff Technical Lead Manager.

Waymo is a pioneering force in autonomous driving technology, dedicated to becoming the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo's mission focuses on creating the Waymo Driver—The World’s Most Experienced Driver™—with the goal of enhancing mobility access and significantly reducing traffic-related fatalities. The Waymo Driver is the backbone of our fully autonomous ride-hailing service and is adaptable across various vehicle platforms and applications. With over ten million rider-only trips completed and the experience of driving autonomously for over 100 million miles on public roads, alongside tens of billions of miles in simulation across more than 15 U.S. states, we are committed to transforming the future of transportation.The Simulator Team at Waymo is at the forefront of innovation, developing advanced simulations that replicate realistic environments for the testing, training, and validation of the Waymo Driver. Our team comprises a diverse, collaborative group of machine learning (ML) engineers, software engineers, and ML research engineers, who are dedicated to crafting industry-leading simulation solutions. Utilizing cutting-edge generative and reconstructive ML algorithms, we model the real world, including realistic agents, road systems, traffic dynamics, weather conditions, and a comprehensive sensor suite (Camera, Lidar, Radar).In this exciting role, you will be instrumental in enhancing the fidelity, scalability, controllability, and richness of our simulations by exploring the latest advancements in 3D world modeling. By leveraging state-of-the-art ML technologies trained on extensive datasets, you will help us create dynamic, semantically rich virtual worlds that have a direct impact on the development and validation of the Waymo Driver.You will report directly to a Senior Staff Engineering Manager.Responsibilities:Lead the design, development, and deployment of innovative 4D world models and generative systems aimed at generating ultra-realistic and controllable sensor outputs and semantics for simulation applications at Waymo.Architect and implement scalable, robust ML pipelines for the training, evaluation, and deployment of large-scale generative models within our simulation framework, employing techniques like model distillation and quantization.Develop and scale production-ready video generation methodologies (e.g., Diffusion, Flow Matching) to create dynamic and interactive simulation environments.Utilize Vision Language Models (VLMs) to enhance semantic comprehension and control within our world simulation products.Collaborate with leading research teams across Waymo and Alphabet to integrate state-of-the-art research in 4D world modeling and generative AI into scalable, production-ready solutions.Provide mentorship and technical guidance to fellow engineers on the team.

About DataVisorDataVisor stands at the forefront of the AI-powered Fraud and Risk Platform industry, delivering unparalleled detection coverage. Our open SaaS platform enables seamless data consolidation and enrichment, equipping organizations with real-time solutions for combating fraud and anti-money laundering (AML) activities. With our patented unsupervised machine learning technology, advanced device intelligence, and robust decision-making tools, DataVisor offers immediate performance enhancements. Our platform is designed for versatility, accommodating multiple use cases across diverse business units while significantly reducing total ownership costs compared to traditional solutions. Recognized as an industry leader, DataVisor serves numerous Fortune 500 companies worldwide.Our award-winning technology is driven by a talented team of experts in big data, machine learning, security, and scalable infrastructure. We foster an open, positive, collaborative, and results-oriented culture. We invite you to be part of our journey!Role SummaryWe are on the lookout for enthusiastic, recently graduated or soon-to-graduate MS or Ph.D. candidates in Computer Science, Machine Learning, Data Science, or related disciplines to join our team as AI/ML Engineering Interns.This internship provides a fantastic opportunity for candidates keen on understanding the construction and deployment of large-scale AI systems in production. You will collaborate with seasoned engineers and data scientists to contribute to the Intelligence Layer and Data Consortium that underpin DataVisor’s real-time fraud detection capabilities.Key areas of focus include distributed systems, data pipelines, machine learning infrastructure, and applied AI, with exposure to agentic flows and large language models (LLMs).What You’ll DoData Engineering & PipelinesAssist in developing and maintaining high-throughput data pipelines utilizing technologies such as Spark, Kafka, or Flink.Support the processing and aggregation of real-time signals (e.g., device fingerprints, behavioral data) into shared intelligence systems.Distributed Systems & ScalabilityLearn to design and optimize backend systems that facilitate large-scale, real-time decision-making.Contribute to enhancing system performance, reliability, and latency during high transaction volumes.AI Applications & Agentic FlowsAssist in developing AI applications and agentic workflows utilizing cutting-edge LLMs (e.g., OpenAI, Anthropic, Google).Explore natural language interfaces, intelligent rule suggestions, and automated strategy generation.Machine Learning PipelinesHelp deploy and monitor pipelines for both unsupervised and supervised ML models.Contribute to the integration of models into real-time applications.

The Role Join our innovative team as a Software Engineer specializing in Agentic AI Systems as a new graduate. If you have developed your programming expertise through internships, research, or academic projects and are eager to apply your skills at the forefront of AI technology, we encourage you to consider this exciting opportunity. As a valued member of our Natural Language Understanding team within the 'agent lab', you will contribute significantly to our mission of enhancing the capabilities that agents can reliably perform at scale. Your work will involve advancing the Moveworks AI Assistant platform in areas including agent orchestration, sandboxed file systems, latency optimization, agent memory, LLM self-improvement, execution environment simulation, enterprise knowledge graphs, and multimodal I/O. Equipped with state-of-the-art enterprise AI tools, including leading LLMs from providers like OpenAI, you will engage in rapid development on scalable infrastructure, tackle challenging engineering problems, and maximize the value we deliver to our customers. If you are excited about making a meaningful impact alongside a dedicated team, we would love to hear from you. What You Will Do: Engage in engineering challenges to build and enhance robust AI agent systems. Implement cutting-edge AI algorithms and architectures, collaborating closely with senior engineers to ensure scalability. Leverage the latest advancements in machine learning, LLMs, and AI to enhance our products and create exceptional user experiences. Contribute to projects that generate lasting value for our clients. Refine your skills in writing efficient, maintainable, and high-performance code. Collaborate with experts across various domains, including machine learning, security, product management, user experience, and customer success, to create the premier enterprise AI product. Learn from and work with senior engineers and machine learning experts to develop world-class AI systems.

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 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.

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.

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.

About EarnInEarnIn is a trailblazer in the field of earned wage access, dedicated to creating innovative solutions that provide real-time financial flexibility for individuals navigating the challenges of living paycheck to paycheck. Our community empowers members to access their earnings as they earn them, offering options to spend, save, and invest without mandatory fees, interest charges, or credit inquiries.With a highly experienced leadership team and backing from esteemed partners such as A16Z, Matrix Partners, DST, and Ribbit Capital, EarnIn is in a strong position with a thriving core business and significant growth potential. We are rapidly expanding and eager to onboard world-class talent to help us shape the future of our organization.POSITION SUMMARYWe are looking for a forward-thinking and experienced Director of Machine Learning to spearhead our machine learning initiatives across the organization. As a fintech leader, machine learning is central to our business strategy and enhances user experience. We rely on advanced, scalable ML systems to make impactful decisions and provide outstanding customer value. Our goal is to revolutionize success stories through the application of generative AI and cutting-edge machine learning algorithms, resulting in significant business and societal outcomes.The Director of ML will prioritize operational excellence by crafting and executing a strategy that transitions ML models from research to production, ensuring optimal performance, reliability, and maintainability. The ideal candidate will have a demonstrated history of deploying ML models at scale, particularly in dynamic startup settings. A strong coding background, familiarity with production-level ML engineering, and the ability to connect theoretical frameworks with practical execution are essential.The base salary range for this full-time role in Mountain View is $414,000 to $506,000, accompanied by equity and benefits. Salary ranges are determined by role, level, and location. This is a hybrid position, requiring in-office work two days a week.

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 world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, we have focused on developing the Waymo Driver—The World’s Most Experienced Driver™—aimed at enhancing mobility access and significantly reducing traffic-related fatalities. The Waymo Driver powers our fully autonomous ride-hail service and is adaptable to various vehicle platforms and use cases. With over ten million rides completed, our technology has autonomously driven more than 100 million miles on public roads and tens of billions of miles in simulation across 15+ U.S. states.The Predictive Planning team (PrePlan) is responsible for crafting and implementing cutting-edge machine learning solutions that forecast future scenarios and dictate the Waymo Driver's actions. Our goal is to harness Waymo’s vast driving data to create robust, generalizable, and high-performing deep neural networks, allowing our autonomous vehicles to navigate intricate environments safely and efficiently.In this hybrid role, you will collaborate closely with our PrePlan team under the guidance of a dedicated manager, with the team assignment occurring post-on-site interviews.

Waymo is pioneering the future of autonomous driving technology with a commitment to becoming the most trusted driver worldwide. Since its inception as the Google Self-Driving Car Project in 2009, Waymo has dedicated itself to developing the Waymo Driver—The World’s Most Experienced Driver™—with the goal of enhancing mobility access and saving countless lives currently lost to traffic accidents. The Waymo Driver not only powers our fully autonomous ride-hail service but is also adaptable across various vehicle platforms and applications. Having completed over ten million rider-only trips and autonomously navigated more than 100 million miles on public roads, our technology has undergone extensive testing, including tens of billions of miles in simulations across more than 15 U.S. states.The Simulator Team at Waymo specializes in creating cutting-edge simulations of realistic environments designed for the rigorous testing and training of the Waymo Driver. Our diverse and collaborative team comprises software engineers, machine learning (ML) engineers, and data scientists, all united in our mission to develop industry-leading simulation solutions utilizing advanced ML algorithms to measure and enhance the Waymo Driver's performance. By leveraging machine learning, we meticulously model real-world scenarios, including realistic agents such as vehicles, pedestrians, cyclists, motorcyclists, roads, traffic control systems, and varying weather conditions.To enhance the fidelity and steerability of our simulations, we integrate the latest ML technologies, including large foundation models trained on our exclusive datasets and advanced diffusion techniques. Our investment in robust infrastructure facilitates the swift setup and deployment of multiple scenarios for comprehensive testing of our autonomous driving systems.In this hybrid role, you will report to a Senior Engineering Manager.

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