Senior/Staff Behavior Prediction Engineer

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, 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 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.

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.

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.

Waymo is at the forefront of autonomous driving technology, striving to become the world’s most reliable driver. Originating from the Google Self-Driving Car Project in 2009, our mission has been to develop the Waymo Driver—the world's most experienced driver—to enhance mobility access and save countless lives lost to traffic accidents. The Waymo Driver powers our fully autonomous ride-hail service and can be adapted to various vehicle platforms and product applications. With over ten million rider-only trips and more than 100 million miles driven autonomously on public roads, along with tens of billions of miles simulated across more than 15 U.S. states, we are redefining transportation.The Perception team is dedicated to building systems that learn the spatial-temporal representations and semantic meanings of the environment around the autonomous driving vehicle (ADV). We collaborate closely with downstream teams to optimize and integrate these systems into the Waymo Driver. Our research tackles real-world challenges and involves collaboration with Alphabet’s research teams. With access to millions of miles of diverse driving data from various sensors, our engineers develop methods for efficient and continuous learning from large-scale real-world data, model training at scale, real-world behavior analysis, and optimizing models for both onboard and offboard hardware.In this hybrid role, you will report to a Technical Lead Manager.

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 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.

Join our dynamic team at Moveworks as a Senior Staff Machine Learning Engineer. In this pivotal role, you will leverage your expertise in machine learning and artificial intelligence to develop and enhance agentic systems that transform the way organizations interact with their customers. You will work alongside a talented group of engineers and data scientists to create innovative solutions that improve user experiences.

Join Our TeamAre you passionate about pioneering projects that harness advanced AI technology to unlock significant benefits from meetings and conversations? Become a vital member of our core AI team at Otter.ai, where you will collaborate with seasoned scientists and engineers dedicated to machine learning. As a Senior Machine Learning Engineer, your expertise in software engineering will be crucial in scaling and refining our machine learning systems. You will play a key role in transforming innovative research into production-ready features that enhance Otter’s summarization and conversational intelligence products.Your ContributionsDesign, construct, and advance extensive SID / ASR / NLP / LLM systems that drive essential product experiences, including summarization, chat, and speech comprehension for millions of interactions.Lead the creation and execution of training, fine-tuning, post-training, and inference methodologies for large language and speech models utilizing PyTorch and/or JAX while balancing quality, latency, cost, and dependability.Innovate and enhance model architectures, loss functions, decoding techniques, and training methodologies for speech and language models, guided by research insights and production restrictions.Oversee the entire ML system lifecycle, from initial research prototyping to production deployment, continuous monitoring, iteration, and long-term maintenance.Collaborate closely with product and infrastructure teams to translate groundbreaking research into scalable, production-grade systems that yield measurable user and business outcomes.Champion system-level enhancements in model performance, robustness, observability, and operational excellence using real-world conversational data.Establish technical direction and best practices for ML infrastructure, data pipelines, evaluation frameworks, and deployment workflows within a cloud environment.Diagnose and resolve complex issues related to model behavior, data quality, scalability, and system interactions, often preemptively before they affect users.Mentor and uplift fellow engineers, contributing to team standards, evaluating designs, and fostering a culture of sound technical decision-making and execution.

About NewsBreakFounded in 2015, NewsBreak is at the forefront of the Content Intelligence platform, revolutionizing the future of the content economy. With over 40 million monthly active users, our flagship platform offers highly personalized local news and information, driven by cutting-edge AI, advanced recommendation systems, and innovative adtech.Honored by Fast Company as #32 on the Top Workplaces for Innovators, we are proud to be Great Place to Work® certified and foster a dynamic team of technologists, product innovators, and business leaders dedicated to tackling meaningful challenges at scale.Having achieved unicorn status in 2021, we are committed to sustaining our high-growth trajectory with a skilled team poised to build the infrastructure layer for content intelligence.If you’re passionate about dreaming big, innovating rapidly, and making a significant impact, we want to hear from you! For more details, visit www.newsbreak.com/aboutAbout the RoleWe seek a Senior Machine Learning Engineer to enhance our large-scale recommendation systems and implement AI/LLM technologies to solve real-world production challenges. You'll engage with our core feed, retrieval, and ranking systems that serve tens of millions of users, while also contributing to AI-driven innovation projects that seek new avenues for improving content discovery, personalization, and developer productivity. This position is perfect for engineers who relish strong individual ownership, hands-on development, and turning concepts into robust systems.What You’ll Work OnLarge-Scale Recommendation SystemsDesign, develop, and refine high-throughput, low-latency recommendation systems that drive NewsBreak’s core feeds.Enhance retrieval, ranking, and multi-objective optimization to strike a balance between engagement, retention, content quality, and business metrics.Oversee systems from offline training to online inference, A/B experimentation, and metric analysis.

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.

About UsNuro is at the forefront of self-driving technology, dedicated to making autonomy available to everyone. Established in 2016, we are developing the world's most scalable driver by merging innovative AI with robust automotive hardware. Our flagship technology, the Nuro Driver™, is licensed to facilitate a variety of applications, from robotaxis to commercial fleets and personal vehicles. With years of successful self-driving deployments, Nuro is paving the way for automakers and mobility platforms to achieve commercial-scale autonomy, enabling a safer, more interconnected future.Role OverviewOur Sensor Data and Calibration team is expanding, and we are seeking a Senior Software Engineer with a strong background in robotics and machine learning. You will be responsible for designing both online and offline unstructured (targetless) sensor calibration algorithms. The ideal candidate will have extensive hands-on experience in the research, development, and application of machine learning methods utilizing various sensor data types (IMU, camera, lidar, radar, etc.). Familiarity with classical state estimation techniques, such as non-linear least-squares optimization and Lie algebra, is a plus.Key ResponsibilitiesDevelop cutting-edge state estimation and calibration algorithms leveraging both traditional robotics and modern machine learning techniques.Evaluate and characterize the accuracy and performance metrics of state estimation and calibration algorithms.Integrate calibration pipelines into the autonomy system while monitoring onboard performance and resource usage.Collaborate with cross-functional teams to enhance ML model training and overall performance assessment.Address critical inquiries regarding sensor data and overall autonomy effectiveness.

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

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

Join Waymo as a Senior Staff Machine Learning Engineer specializing in Depot Automation, where you will play a vital role in transforming the future of transportation through cutting-edge machine learning solutions.Your expertise will drive innovation and efficiency, ensuring our autonomous vehicles operate seamlessly in various environments. Collaborate with a team of passionate engineers and researchers to develop and implement advanced algorithms that enhance our depot operations.

About NewsBreakFounded in 2015, NewsBreak is a pioneering Content Intelligence platform that is redefining the content economy. With a vibrant community of over 40 million monthly active users, our flagship platform offers deeply personalized local news and information, driven by cutting-edge AI technologies, sophisticated recommendation systems, and innovative adtech solutions.Recognized by Fast Company as #32 on the Top Workplaces for Innovators, we take pride in being Great Place to Work® certified. Our dynamic team of technologists, product innovators, and business leaders is dedicated to tackling significant challenges at scale.Having reached unicorn status in 2021, we are steadfast in our commitment to maintaining a high-growth trajectory through the right talent to help us realize our mission: building the infrastructure layer for content intelligence.If you’re motivated to think big, innovate rapidly, and make a meaningful impact, we’d love to connect with you! For more information, visit www.newsbreak.com/aboutAbout the RoleWe are on the lookout for a Staff Machine Learning Engineer to spearhead technical leadership for our recommendation systems and AI initiatives.In this pivotal position, you will set the technical direction for large-scale personalization systems, lead intricate projects across various teams, and champion the integration of AI / LLM technologies in our product capabilities and engineering workflows.This opportunity is perfect for engineers who relish system-level thinking, enjoy mentoring others, and excel at transforming complex, ambiguous challenges into scalable solutions.What You’ll Work OnTechnical Leadership & ArchitectureLead the design of next-generation recommendation system architectures at scale.Drive best practices for model lifecycle management, experimentation, and system reliability.Collaborate with product, infrastructure, and data teams to ensure alignment of technical strategy with business objectives.Advanced Recommendation & AI SystemsOversee complex initiatives encompassing retrieval, ranking, re-ranking, and multi-objective optimization.

The OpportunityAre you passionate about leading innovative projects that harness AI technology to enhance the value of meetings and conversations? Join our dynamic AI team at Otter.ai, where you will collaborate with seasoned scientists and engineers to advance our machine learning capabilities. As a Senior Machine Learning Engineer, you will leverage your robust software engineering expertise to scale and optimize our ML systems, transforming pioneering research into production-ready features that drive our summarization and conversational intelligence offerings.Your ImpactDesign, build, and advance expansive Speech Recognition, Natural Language Processing, and Large Language Model systems that underpin essential product experiences, including chat and speech understanding across millions of interactions.Lead the architecture and development of training, fine-tuning, post-training, and inference methodologies for large-scale language and speech models utilizing PyTorch and/or JAX, making informed trade-offs among quality, latency, cost, and reliability.Enhance model architectures, loss functions, decoding methods, and training strategies for speech and language models, guided by both research insights and practical constraints.Oversee the complete ML system lifecycle, from research prototyping to production deployment, including monitoring, iteration, and ongoing maintenance.Collaborate closely with product and infrastructure teams to translate groundbreaking research into scalable, production-grade systems that yield significant user and business impact.Drive enhancements in model performance, reliability, observability, and operational excellence using real-world conversational data at scale.Establish technical direction and best practices for ML infrastructure, data pipelines, evaluation frameworks, and deployment processes in a cloud environment.Identify and resolve complex challenges in model behavior, data quality, scaling, and system interactions, often preemptively addressing issues before they affect users.Mentor and uplift fellow engineers, shaping team standards, reviewing designs, and fostering a culture of high-quality technical decision-making and execution.Influence applied research and technical strategies by pinpointing promising speech and multimodal modeling techniques, and driving their validation and adoption.

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