Machine Learning Engineer - Mapping

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

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

As the Engineering Manager for the Machine Learning Infrastructure team, you will lead the charge in developing a state-of-the-art platform that underpins Moveworks' conversational AI capabilities. This pivotal role is essential for the long-term scalability of our flagship AI product and the overall success of the company.Your primary responsibility will be to oversee a team of skilled engineers dedicated to constructing, optimizing, and expanding the comprehensive systems that facilitate the entire ML/LLM lifecycle. This encompasses our infrastructure for distributed training and inference, model evaluation frameworks, and LLM latency optimization. You will shape the technical direction of the team, harmonizing the operational requirements of our core ML infrastructure with innovative research to create the next generation of LLMs utilizing advanced generative AI.The frameworks your team creates will form the backbone for all ML models deployed in production, serving hundreds of millions of enterprise employees. Your efforts will significantly influence the evolution of the Moveworks Enterprise Copilot platform and the trajectory of AI-driven employee services.

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

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

Waymo is a pioneering company in the autonomous driving sector, dedicated to becoming the world’s most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has been committed to developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and prevent traffic-related fatalities. With over ten million rider-only trips and more than 100 million miles driven autonomously across various U.S. states, Waymo continues to push the boundaries of what is possible in vehicular automation. Our DUE Machine Learning team is tasked with constructing and managing scalable machine learning and data systems, simulation workflows, and insight tools, all aimed at optimizing the evaluation and onboarding processes for developers. This team integrates human expertise with cutting-edge machine learning models to produce training and evaluation data across a multitude of metrics, enhancing the performance of the Waymo Driver. We seek passionate researchers and software engineers excited about advancing machine learning methodologies for our autonomous vehicle evaluation systems, dedicated to enhancing our technology stack's efficacy.

Role Overview Waymo is hiring a Machine Learning Engineer focused on infrastructure for driver understanding and evaluation. This position is based in Mountain View, CA. What You Will Do Work closely with a team to advance autonomous driving systems. Develop and maintain infrastructure that supports machine learning models for vehicle perception and environmental interaction. Apply expertise in building and scaling machine learning solutions that help vehicles interpret and respond to their surroundings. About the Team This group focuses on improving how autonomous vehicles understand and evaluate driver behavior, aiming to make self-driving technology safer and more effective.

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

Waymo is looking for a Senior Machine Learning Engineer focused on Runtime and Serving to help advance autonomous vehicle technology in Mountain View, CA. Role overview This position centers on developing and improving machine learning systems that support safe and efficient vehicle operation. The work involves optimizing algorithms and increasing the performance of deployed models in real-world conditions. What you will do Lead the design and implementation of machine learning systems used in autonomous vehicles Work on runtime and serving infrastructure to ensure reliable and efficient model deployment Contribute expertise to optimize algorithms for safety and operational performance Impact Your contributions will directly affect how Waymo's vehicles interpret and respond to their environment, supporting safer and more reliable autonomous driving.

Waymo is at the forefront of autonomous driving technology, dedicated to becoming the world’s most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has been 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.

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.

Role Overview Waymo is hiring a Senior Machine Learning Engineer for its Infrastructure team in Mountain View, CA. This position centers on advancing Driver Understanding and Evaluation systems that support autonomous driving technology. What You Will Do Develop and refine machine learning algorithms to boost the accuracy and efficiency of Waymo's self-driving systems. Work closely with engineers and specialists across teams to design and implement technical solutions for Driver Understanding and Evaluation. Contribute to infrastructure that supports large-scale machine learning in the automotive domain. Collaboration This role involves regular collaboration with cross-functional groups, bringing together expertise from multiple disciplines to improve AI-driven vehicle performance.

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.

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.