Machine Learning Engineer - Perception

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.

About Waymo Waymo develops autonomous driving technology with the goal of making transportation safer and more accessible. Originally launched in 2009 as the Google Self-Driving Car Project, Waymo has logged over 100 million autonomous miles and completed more than ten million rider-only trips. The company focuses on building the Waymo Driver to support safe, efficient travel across a range of vehicle platforms. Team Overview: Prediction & Planning - System Architecture The Predictive Planning (PrePlan) team builds machine learning systems that help the Waymo Driver anticipate possible scenarios and plan actions accordingly. By transforming large-scale driving data into robust deep neural networks, the team enables vehicles to navigate complex, real-world environments with confidence. The system architecture group ensures these models work smoothly within Waymo's technology stack. This includes attention to kinematics, interfaces, and data representations. The team works across projects involving data pipelines, model integration, evaluation metrics, and the planner systems that guide autonomous vehicles. Role Details Title: Staff Machine Learning Engineer, Prediction & Planning - System Architecture Location: Mountain View, CA; San Francisco, CA; New York City, NY (hybrid) Reports to: 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, our focus has been on developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and save lives currently lost in traffic incidents. With over ten million rider-only trips facilitated by our technology, and more than 100 million miles driven autonomously on public roads, we are transforming transportation across 15+ U.S. states.The Predictive Planning team (PrePlan) is responsible for designing and implementing advanced machine learning solutions that forecast future world states and plan the Waymo Driver’s actions. Our goal is to harness Waymo’s extensive driving data to create robust, adaptable, and efficient deep neural networks that empower our autonomous vehicles to navigate complex environments safely.In this hybrid position, you will collaborate closely with our PrePlan team and be matched with your team after completing onsite interviews.Your Responsibilities Will Include:Developing cutting-edge ML-driven prediction and planning systems to boost the capabilities of our ML driver and facilitate the rapid growth of Waymo’s services.Converting open-ended, real-life challenges into well-defined ML problems, researching and applying state-of-the-art ML techniques, such as foundation models and reinforcement learning, to enhance autonomous vehicle planning and prediction.Collaborating with top-tier researchers, engineers, and product managers to ensure safe and smooth planning behaviors for all road users, aligning with product specifications.Creating and assessing large-scale models, integrating them into Waymo’s production planning software for real-world applications in close cooperation with the Planner and Research teams.

About the Role Waymo is looking for a Senior Machine Learning Engineer focused on Prediction & Planning to join the System Architecture team. This position is based in Mountain View, CA, San Francisco, CA, or New York City, NY. What You Will Do Design and implement advanced machine learning algorithms for autonomous vehicle prediction and planning. Develop systems that improve the safety and efficiency of self-driving technology. Collaborate with engineers and researchers across teams to advance core capabilities in autonomous driving. Impact Your work will help shape the systems that guide Waymo’s vehicles, supporting safer and more reliable autonomous transportation.

Who We AreNuro is at the forefront of self-driving technology, dedicated to making autonomy accessible for everyone. Founded in 2016, we are developing the most scalable autonomous driving system, merging advanced AI with automotive-grade hardware. Our flagship technology, the Nuro Driver™, is licensed for various applications, including robotaxis, commercial fleets, and personal vehicles. With years of successful deployments, Nuro provides automakers and mobility platforms a clear pathway to commercial-scale autonomous vehicles, paving the way for a safer and more connected future.About the RoleThe Prediction team is tasked with leveraging cutting-edge machine learning techniques to enhance the functionality of the Nuro Driver. As a pivotal member of the Prediction and Smart Agents team, your role will center on developing state-of-the-art models that predict the behavior of surrounding traffic, which are integral to our autonomous systems. These models will be utilized both on-board and off-board in realistic closed-loop simulations.In this position, you will delve into innovative machine learning approaches to address complex challenges in autonomous driving. Your work will involve employing generative sequence modeling techniques to accurately predict intricate, interactive traffic scenarios. This necessitates a deep understanding of the intentions of other road users and their impact on safe driving decisions. You will also explore diverse input modalities, including End-to-End (E2E) strategies, to forecast the behavior of other agents. A crucial aspect of this role is the creation of intelligent, controllable agents to facilitate effective closed-loop training within simulations.If you are driven by the challenge of solving complex problems, leading impactful research, and witnessing your contributions in real-world applications, we invite you to apply!About the WorkDesign and develop scalable, machine learning-based prediction systems to generate multi-modal, realistic, and kinematically feasible trajectories.Engage in pioneering research focused on generative sequence modeling and sequential decision-making, exploring areas such as:Scalable generative sequence modeling techniques.Modeling marginal, conditional, and joint distributions for interactive agents.Transformer-based encoder-decoder frameworks.Large generative models and diffusion techniques.Agent controllability through conditioning, guidance, and various methodologies.Collaborate closely with the Planning team to create realistic and controllable agents that enhance our simulation capabilities.

Who We Are Nuro is a pioneering self-driving technology company dedicated to making autonomy accessible to everyone. Established in 2016, we are developing the most scalable autonomous driving solution, merging advanced AI with high-performance automotive hardware. Our flagship technology, the Nuro Driver™, is licensed for various applications including robotaxis, commercial fleets, and personal vehicles. With years of proven self-driving deployments, Nuro provides automakers and mobility platforms with a clear trajectory towards commercial-scale AVs, fostering a safer, more connected future. About the Role Join our learned behavior team where we leverage sophisticated machine learning strategies to expedite software advancements. This role involves close collaboration with software teams to identify challenges and implement innovative machine learning approaches to tackle real-world problems. Your work may include self-supervised learning for robust representation, out-of-distribution detection for addressing long-tail issues, refining reinforcement learning methods for motion planning, trajectory prediction, and enhancing model robustness to address uncertainties. If you are passionate about solving complex problems with practical solutions ready for vehicle deployment, we invite you to be a part of our journey! About the Work Develop scalable machine learning systems for planning and predicting safe, feasible trajectories for autonomous vehicles. Investigate generative sequence modeling and sequential decision-making; backgrounds in Embodied AI for robotics, Causal reasoning, Model interpretability, and Joint prediction and planning are advantageous. Address uncertainties arising from interconnected autonomous systems. Collaborate across autonomy teams to create comprehensive solutions for major autonomy challenges by understanding issues, proposing ideas, prioritizing tasks, and developing effective solutions. Implement practical solutions and deploy them on real-world vehicles. About You You possess extensive expertise and experience in one or more of the following areas: M.Sc. or Ph.D. in Computer Science, Artificial Intelligence, Mathematics, or a related discipline. Strong background in sequential decision-making, Imitation Learning, Deep Reinforcement Learning, generative modeling, and more.

About Us Gatik is at the forefront of transforming B2B supply chain logistics with our innovative autonomous transportation-as-a-service (ATaaS) solution. We are committed to ensuring safe and reliable deliveries while enhancing freight movement efficiency by mitigating congestion. Notably, in 2021, we launched the world’s first fully driverless commercial transportation service in collaboration with Walmart. Our Class 3-7 autonomous trucks are operational in key markets such as Texas, Arkansas, and Ontario, Canada, driving significant advancements in freight transportation. Our proprietary Level 4 autonomous technology, Gatik Carrier™, is expertly designed to facilitate the safe and efficient transport of goods between pick-up and drop-off points on the middle mile. With advanced capabilities for both highway and urban environments, Gatik Carrier™ integrates cutting-edge software and hardware, seamlessly merging into our customers' logistics operations. Position Overview We are seeking experienced Machine Learning engineers specializing in classical and modern machine learning techniques for behavior prediction. The selected candidate will play a pivotal role in architecting, designing, implementing, and delivering a multi-modal prediction system. Ideal candidates will have a proven track record of guiding processes from research and development through to product launch, creating impactful real-world solutions. This role requires on-site work at our Mountain View, CA office, five days a week. Key Responsibilities Develop critical components of the behavior prediction system, focusing on accurately forecasting the movements and actions of surrounding objects to enhance the decision-making capabilities of our autonomous vehicles. Collaborate closely with cross-functional teams to integrate prediction models into our existing systems. Conduct research to continuously improve prediction accuracy and system performance.

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.

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.

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.

Waymo, a leader in autonomous driving technology, is dedicated to becoming the world’s most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has developed the Waymo Driver—The World's Most Experienced Driver™—to enhance mobility access and drastically reduce traffic-related fatalities. With over ten million rider-only trips and the ability to autonomously navigate more than 100 million miles on public roads, Waymo is transforming transportation across 15+ U.S. states.The Waymo Mapping team aims to create a high-resolution map of the world to facilitate safe autonomous driving. We employ both automated and manual mapping techniques and develop the necessary infrastructure to store, process, and distribute our maps. Our team collaborates with several other departments within Waymo that utilize map data.In this role, you will:Design, train, and deploy machine learning models that automate the creation of Waymo's HD maps, allowing for scalability in the Waymo Driver.Utilize and advance cutting-edge ML techniques, including Vision-Language Models (VLMs) and Generative AI, to innovate in mapping automation.Manage the entire model development lifecycle, from data mining and processing to model training, evaluation, validation, and production.Work closely with partner ML teams, such as Waymo Perception and Waymo AI Foundations, to implement pioneering research into scalable, reliable, production-ready solutions.

Waymo is at the forefront of autonomous driving technology, dedicated to becoming the most trusted driver in the world. Originating from the Google Self-Driving Car Project in 2009, Waymo has made significant strides in developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility and save lives lost in traffic accidents. Our technology powers a fully autonomous ride-hailing service and is adaptable across various vehicle platforms and applications. With over ten million rider-only trips and 100 million miles driven autonomously on public roads, our experience is unmatched.As part of the DUE ML Core team, you will play a pivotal role in building and managing scalable machine learning and data systems, refining simulation workflows, and enhancing developer onboarding experiences. This position combines expert human insight with cutting-edge machine learning models to produce training and evaluation data for a multitude of metrics and components integral to the Waymo Driver. We seek passionate researchers and software engineers eager to advance machine learning methodologies for our autonomous vehicle evaluation systems and continuously improve the performance of our technological framework.

Are you driven by a passion for solving complex AI challenges and eager to play a pivotal role in revolutionizing enterprise automation? Join Kognitos as we shape the future of software development!Your Contributions Will Include:Optimizing Resource Utilization: Create cutting-edge strategies to enhance resource efficiency in training and fine-tuning machine learning models, ensuring optimal performance without compromising on resource usage.Developing Intelligent Workflows: Innovate workflows that empower AI to reason, plan, and execute tasks consistently, reducing errors and unexpected outcomes.Integrating Multimodal Language Models: Engage in multimodal projects that blend text, images, and various data formats to develop robust, enterprise-ready automation solutions.Enterprise-Scale AI Solutions: Deliver AI systems that address enterprise needs, targeting a reduction of operational costs by 30% through widespread adoption.Key Responsibilities:Design and implement machine learning models with a focus on intelligent workflows and reliable task execution.Refine AI systems for multimodal applications, effectively tackling real-world challenges faced by enterprises.Pioneer new fine-tuning methodologies to enhance resource utilization and model efficacy.Ensure alignment of AI systems with regulatory standards while delivering consistent business outcomes.Collaborate with diverse teams, including product management, engineering, and business stakeholders, to drive impactful solutions.Stay abreast of the latest advancements in AI research, integrating cutting-edge developments into Kognitos’ platform.Qualifications:A Bachelor's, Master's, or Ph.D. in Computer Science, Machine Learning, or a related discipline.Demonstrated experience in developing and deploying machine learning models in production settings.Expertise in fine-tuning techniques for large-scale models and resource optimization.Strong intuition and experience with Large Language Models (LLMs).Familiarity with multimodal language models and their applications in enterprise environments.