Fellow - Autonomy (Distinguished Engineer)

🏢 Summary: The offer is for a Machine Learning Systems Engineer focused on optimizing large-scale distributed training systems for frontier models. The role centers on performance profiling, GPU kernel development, and improving throughput, scalability, and reliability of ML training pipelines. It directly supports accelerating model convergence through high-performance systems engineering. 🗂️ Requirements: Bachelor’s, Master’s or PhD in Computer Science, Computer Engineering or related field, Strong proficiency in Python, Extensive hands-on experience with PyTorch, Experience with distributed training using PyTorch Distributed, Experience optimizing ML model training and inference performance, Experience with GPU kernel development in CUDA or Triton, Ability to perform performance profiling and bottleneck analysis, Strong understanding of machine learning concepts and architectures 📃 Skills: Python, PyTorch, CUDA, Triton, Nsight, PyTorchDistributed, GPU, KernelFusion, Sharding, Tiling 🏢 Description: Mission Summary:We are looking for a Machine Learning Systems Engineer to join our ML Acceleration team. In this role, you will be responsible for the core systems that enable our researchers to train frontier models at scale, focusing obsessively on speed, cost, reliability, and throughput. You will work at the intersection of machine learning research and high-performance systems engineering. Your work will directly impact our ability to scale large-scale distributed model training and reduce the time-to-convergence for our next generation of models. What you'll be doing: Performance Profiling & Optimization: Utilize profiling tools (e.g., Nsight, PyTorch Profiler) to identify bottlenecks in data loading, gradient computation, and communication. Implement optimizations like kernel fusion, sharding, and tiling to improve step time. Distributed Training: Optimize distributed training pipelines using frameworks such as PyTorch Distributed. Kernel Development: Design and maintain high-performance GPU kernels in Triton or CUDA for state-of-the-art ML workloads. Data Pipeline Engineering: Optimize robust data loading pipelines that maximize training throughput. What we're looking for: Education: Bachelor's, Master's degree, or PhD in Computer Science, Computer Engineering, or a related technical discipline. Software Engineering: Strong proficiency in Python. ML Frameworks: Extensive hands-on experience with PyTorch. ML Knowledge: Experience optimizing machine learning model execution during training and inference, alongside a strong understanding of fundamental machine learning concepts, architectures, and processes. Problem Solving: Exceptional analytical and problem-solving skills, with a bias for action and a data-driven approach to technical challenges. We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process. Candidates for certain positions are eligible to participate in Motional's benefits program. Motional's benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.Salary Range$144,000—$192,000 USDMotional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We're driven by something more. Our journey is always people first. We aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a technology with the potential to transform the way we move. Higher purpose, greater impact. We're creating first-of-its-kind technology that will transform transportation. To do so successfully, we must design for everyone in our cities and on our roads. We believe in building a great place to work through a progressive, global culture that is diverse, inclusive, and ensures people feel valued at every level of the organization. Diversity helps us to see the world differently; it's not only good for our business, it's the right thing to do. Scale up, not starting up. Our team is behind some of the industry's largest leaps forward, including the first fully-autonomous cross-country drive in the U.S, the launch of the world's first robotaxi pilot, and operation of the world's longest-standing public robotaxi fleet. We're driven to scale; we're moving towards commercialization of our technology, and we need team members who are ready to embrace change and challenges. Formed as a joint venture between Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives. Headquartered in Boston, Motional has operations in the U.S and Asia. For more information, visit www.Motional.com and follow us on Twitter, LinkedIn, Instagram and YouTube. Motional AD Inc. is an EOE. We celebrate diversity and are committed to creating an inclusive environment for all employees. To comply with Federal Law, we participate in E-Verify. All newly-hired employees are queried through this electronic system established by the DHS and the SSA to verify their identity and employment eligibility.

🏢 Summary: Lead the Behaviors (Prediction and ML Planner) team to design and deploy advanced machine learning models for motion planning and agent behavior prediction in Level 4 autonomous vehicles. The role focuses on improving safety, comfort, and legality of self-driving systems through deep learning, generative AI, and reinforcement learning. You will manage engineers, drive large-scale ML initiatives, and productionize solutions on autonomous vehicle fleets. 🗂️ Requirements: Master’s or Ph.D. in Computer Science or related technical field or equivalent industry experience, Proven leadership experience managing and leading engineering teams, Extensive experience executing large, complex technical initiatives, Experience with deep learning frameworks such as TensorFlow or PyTorch, Fluency in Python and scientific computing libraries, Proven experience designing, developing, and deploying ML solutions for autonomous vehicles or robotics, Advanced knowledge of software engineering principles, source control, build processes, code reviews, and testing methods, Strong communication and interpersonal skills 📃 Skills: Python, TensorFlow, PyTorch, C++, CUDA, MachineLearning, DeepLearning, GenerativeAI, ReinforcementLearning, EmbeddedSystems, RealTimeOptimization, SoftwareEngineering, Git 🏢 Description: On the Behaviors team (Prediction and ML Planner), you will work on machine learning models that enable self-driving vehicles to navigate complex real-world traffic scenarios. The team develops models to set the behavior of autonomous vehicles and predict the behavior of other agents such as vehicles and vulnerable road users. What You'll Be Doing: - Define and execute motion planning and prediction projects to improve the vehicle's ability to safely, comfortably, and legally navigate complex traffic scenarios - Lead, manage, and grow a team of engineers - Design and lead the implementation of behavior models leveraging advancements in machine learning, generative AI, and reinforcement learning - Productionize and deploy solutions onto autonomous vehicle fleets - Collaborate with perception, simulation, data platform, and integration teams to validate and enhance on-road performance - Communicate strategies, progress, and challenges to executive leadership What We're Looking For: - Masters or Ph.D. in Computer Science or a related technical field; or equivalent industry experience - Proven leadership skills executing large, complex technical initiatives - Extensive experience managing and leading engineers - Experience with deep learning frameworks such as TensorFlow or PyTorch - Fluency in Python, including standard scientific computing libraries - Proven track record of designing, developing, and deploying ML solutions for autonomous vehicles or robotics - Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, and testing methods - Excellent communication and interpersonal skills Bonus Points: - Experience with embedded systems and real-time optimization, especially in the autonomous driving industry - Experience with state-of-the-art generative AI and/or reinforcement learning paradigms - Publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, ICL, etc.) - Strong programming skills in C++ and/or CUDA programming Compensation and Benefits: The salary range for this role is $240,000—$330,000 USD base salary. Additional compensation may include bonus or company equity. Benefits may include medical, dental, vision, 401k with company match, health savings accounts, life insurance, pet insurance, and more.

🏢 Summary: Senior Machine Learning Engineer role focused on developing and deploying deep learning solutions for prediction, planning, and control within an autonomous driving platform. The position involves leading experiments, building large-scale production ML systems, and collaborating with cross-functional teams to deliver industrial-grade models. It requires extensive experience in autonomous vehicles or robotics and deep expertise in modern ML frameworks and large language models. 🗂️ Requirements: BS/MS/PhD in Computer Science, Electrical Engineering, Mechanical Engineering, Applied Math or related field, 15+ years of experience building ML systems for autonomous vehicles or robotics, Deep understanding of large language models and transformers, Hands-on experience building and deploying large-scale production ML systems, Experience with DNN training, inference and optimization, Strong mathematical foundation in machine learning and deep learning, Proven leadership and innovation track record 📃 Skills: Python, MachineLearning, DeepLearning, LLM, Transformers, PyTorch, TensorFlow, TensorRT, DNN, Robotics, AutonomousVehicles 🏢 Description: What you'll be doing: Researching, implementing, and evaluating deep-learning-based methods for prediction and planning for Autonomous Vehicle products. Leading, designing, running, and analyzing experiments and testing to evaluate the efficiency of solutions on real-world data. Partnering with system software engineering specialists to ship industrial strength ML models. Communicating and collaborating with multi-functional teams. What We're Looking For: BS/MS/PhD in computer science, electrical engineering, mechanical engineering, applied math, or related fields (or equivalent experience) 15+ years of proven experience building ML systems for autonomous vehicles or similar robotics applications Deep understanding of large language models (LLM) and transformers Hands-on experience building large scale production ML systems and deploying them at scale Excellent leadership and track record for innovation to help build the next generation of ML-based planning solutions Experience with deep neural network (DNN) training, inference and optimization in leading frameworks (Pytorch, Tensorflow, TensorRT, etc.) Excellent understanding of the mathematical foundations of machine learning and deep learning Bonus Points: Prior experience as a ML planning lead Proven publication record in ML for planning, vision, or related fields Prior experience building and deploying vision language action or chain of thought models Benefits: Salary range: $271,000—$373,000 USD (base salary) Eligibility to participate in benefits program including medical, dental, vision, 401k with company match, health savings accounts, life insurance, pet insurance, and more.

🏢 Summary: Senior technical role in the Planning team focused on leading research, architecture, and development of advanced motion planning and control systems for autonomous vehicles operating in complex environments. The position drives algorithm innovation, system integration, and production deployment while mentoring engineers and collaborating cross-functionally. Ideal for an expert in robotics and high-performance C++ development with extensive experience in motion planning and probabilistic decision-making. 🗂️ Requirements: PhD in Robotics, Computer Science, Computer Engineering, Mechanical Engineering or related field OR Master’s degree with 7+ years robotics experience, 10+ years research experience in robotics or motion planning, 5+ years professional C++ software development experience, Proven experience leading complex technical projects from research to production deployment, Experience developing high-performance, reliable systems, Experience architecting and integrating motion planning algorithms, Strong background in probabilistic approaches for decision-making under uncertainty 📃 Skills: C++, Robotics, MotionPlanning, Algorithms, ProbabilisticModels, GaussianMixtureModels, HiddenMarkovModels, ParticleFilters, MachineLearning, BayesianModeling, Bazel, TrajectoryOptimization, ControlSystems, Prediction, SearchAlgorithms, GeometryAlgorithms 🏢 Description: Description: Motional is seeking a technical expert for its Planning team to define motion planning and control systems for secure, effective, and comfortable fleet operation in complex environments. This role requires expertise in cutting-edge research, advanced algorithm development, and robust software building to generate safe, comfortable, and intuitive routes and motions. The position focuses on contributing to production-ready autonomous vehicles through innovative and scalable planning solutions. Role Responsibilities: - Lead the research and development of novel algorithms and sub-systems for motion planning in autonomous driving, expanding the Operational Design Domain, including advanced search-based and geometry-based methods and probabilistic decision-making under uncertainty. - Lead cross-functional projects to define new or upgrade existing interfaces to solve problems. - Monitor overall system performance, identify improvement areas, and develop technical strategies to address deficiencies. - Guide cross-functional teams to deliver comprehensive solutions beyond the planning system scope. - Architect and integrate complex combinations of motion planning and prediction algorithms for real-world deployment. - Design and build a robust, scalable, high-performance codebase enabling rapid prototyping and rigorous evaluation. - Collaborate with perception and prediction components upstream and trajectory optimization, tracking, and control components downstream to ensure end-to-end system performance. - Promote strong software engineering practices and mentor junior and senior engineers. Requirements: - PhD preferred in Robotics, Computer Science, Computer Engineering, Mechanical Engineering, or related field; or Master’s degree with 7+ years of robotics experience. - 10+ years of research experience in robotics or motion planning with a track record of state-of-the-art contributions. - 5+ years of C++ software development focused on high-performance and reliable systems. - Experience leading complex features from problem formulation through deployment in production environments. Preferred Skills: - Experience with probabilistic models such as Gaussian Mixture Models, Hidden Markov Models, and Particle Filters. - Experience with machine learning techniques including Bayesian modeling and inference for decision-making under uncertainty. - Experience with Bazel build framework. Compensation and Benefits: - Salary range: $240,000–$330,000 USD (base salary). - Eligibility for additional compensation such as bonus or company equity. - Benefits may include medical, dental, vision, 401k with company match, health savings accounts, life insurance, pet insurance, and more.

🏢 Summary: Senior-level ML engineering role focused on defining architecture and technical strategy for large-scale multimodal machine learning systems powering data discovery and model improvement in autonomous driving. The position leads cross-functional initiatives, builds scalable data mining and real-time inference frameworks, and sets engineering standards across the organization. It combines hands-on system design with technical leadership and mentorship. 🗂️ Requirements: BS in Computer Science, Machine Learning or related field (or equivalent experience), 8+ years of hands-on ML engineering experience, Proven ownership of architecture, deployment and optimization of large-scale ML systems, Experience with multimodal foundation models in production (integration, scaling, fine-tuning, deployment), Demonstrated technical leadership across multi-quarter, multi-person initiatives, Expert-level Python proficiency, Strong experience with PyTorch, TensorFlow or JAX, Strong software engineering fundamentals (system design, CI/CD, containerization), Experience deploying ML models in AWS, GCP or Azure, Experience optimizing ML systems for latency, throughput and hardware efficiency, Ability to mentor engineers and drive cross-team technical alignment 📃 Skills: Python, PyTorch, TensorFlow, JAX, AWS, GCP, Azure, CI/CD, Docker, Kubernetes, GPU, CPU, DeepLearning, ActiveLearning, GenerativeAI, MLOps, Triton, TorchServe, TFServing 🏢 Description: Mission Summary: At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery. As a Staff Machine Learning Engineer, you will serve as a technical leader defining the roadmap and architecture for the machine learning systems that power our data discovery and model improvement lifecycles. Rather than focusing on a single specialized domain, you will leverage your broad ML expertise to architect massive, scalable systems, from multimodal representation learning and active learning loops to hyper-efficient production inference. You will own system-level architecture, lead multi-quarter, multi-person initiatives, and partner across the engineering organization to unblock teams and influence department-wide technical strategy. By establishing robust processes and mentoring others, you will ensure ML platforms act as a reliable, mission-critical engine for the autonomy stack. What You'll Do: Define Technical Strategy & Roadmaps: - Develop and execute multi-quarter, high-impact technical roadmaps for core ML systems - Inform leadership to guide reprioritization aligned with OKRs and KPIs Architect System-Level Solutions: - Own system-level architecture for complex ML products - Design scalable frameworks for massive data mining and optimized real-time inference across GPU/CPU clusters Drive Cross-Functional Execution: - Lead multi-person projects across teams to completion - Influence partner team roadmaps to solve shared problems and build alignment Elevate Engineering Excellence: - Establish standards for ML system design, code quality, testing and deployment - Deliver processes to proactively address issues and participate in incident response planning Operate as a Generalist Expert: - Apply deep learning, representation learning, active learning and generative AI techniques to complex problems - Unblock teams facing unprecedented technical challenges Mentor and Lead: - Coach senior and junior engineers - Lead architectural reviews and contribute to engineering culture through documentation and tech talks What We're Looking For (Must-Haves): - BS in Computer Science, Machine Learning or related field (or equivalent practical experience) - 8+ years of hands-on ML engineering experience with large-scale ML systems - Experience with multimodal foundation models in production systems (camera, LiDAR, radar, text) - Demonstrated technical leadership across multi-quarter initiatives - Expert-level Python and experience with PyTorch, TensorFlow or JAX - Strong software engineering fundamentals including system design, CI/CD and containerization - Experience deploying ML models in AWS, GCP or Azure and optimizing for latency and throughput - Proven ability to mentor peers and drive consensus across teams Bonus Points: - MS or PhD in Computer Science, Machine Learning or related field - Background in autonomous driving, robotics or real-time decision-making systems - Experience with large-scale ML data mining, active learning loops and representation learning - Familiarity with multimodal learning, sensor fusion or large foundation models - Experience with model serving tools such as TF Serving, Triton or TorchServe - Experience leading severity reviews or establishing incident response processes for ML platforms Work Arrangement: Hybrid schedule with in-office time in Boston, Pittsburgh or Las Vegas, or fully remote. Compensation & Benefits: Salary range: $205,000—$272,500 USD (base salary). Additional compensation may include bonus or company equity. Eligible employees may participate in benefits including medical, dental, vision, 401k with company match, health savings accounts, life insurance and pet insurance.

🏢 Summary: Lead the research, architecture, and deployment of advanced motion planning and control systems for production autonomous vehicles operating in complex environments. The role focuses on developing state-of-the-art probabilistic and search-based algorithms, building high-performance C++ systems, and driving cross-functional integration across the full autonomy stack. Ideal for a senior robotics expert passionate about scaling safe and comfortable autonomous driving solutions. 🗂️ Requirements: PhD in Robotics, Computer Science, Computer Engineering, Mechanical Engineering, or related field; or Master’s degree with 7+ years robotics experience, 10+ years research experience in robotics or motion planning, 5+ years C++ development experience in high-performance, reliable systems, Proven experience leading complex technical features from research to production deployment, Experience developing motion planning algorithms for autonomous systems 📃 Skills: C++, Robotics, MotionPlanning, Algorithms, ProbabilisticModels, GaussianMixtureModels, HiddenMarkovModels, ParticleFilters, MachineLearning, BayesianInference, Bazel, TrajectoryOptimization, ControlSystems 🏢 Description: Description Motional is seeking a technical expert for its Planning team to define motion planning and control systems for secure, effective, and comfortable fleet operation in complex environments. This role requires expertise in cutting-edge research, advanced algorithm development, and robust software building to generate safe, comfortable, and intuitive routes and motions. The position focuses on contributing to production-ready autonomous vehicles. Role Responsibilities - Lead the research and development of novel algorithms and sub-systems for motion planning in autonomous driving, expanding the Operational Design Domain, including advanced search-based and geometry-based methods and probabilistic decision-making under uncertainty. - Lead cross-functional projects to define new or upgrade existing interfaces. - Monitor overall system performance, identify areas for improvement, and develop technical strategies to address deficiencies. - Guide cross-functional teams to deliver comprehensive solutions beyond the planning system scope. - Architect and integrate motion planning and prediction algorithms, driving evaluation and refinement for real-world deployment. - Design and build a robust, scalable, high-performance codebase for rapid prototyping and rigorous evaluation. - Collaborate with perception, prediction, trajectory optimization, tracking, and control teams to ensure end-to-end system performance. - Mentor and guide team members, promoting product-focused engineering and rigorous research. What We’re Looking For - PhD preferred in Robotics, Computer Science, Computer Engineering, Mechanical Engineering, or related field; or Master’s degree with 7+ years of robotics experience. - 10+ years of research experience in robotics or motion planning with demonstrated impact. - 5+ years of C++ software development experience building high-performance and reliable systems. - Experience leading technical development from problem formulation through research, implementation, and production deployment. - Strong drive for innovation and technical leadership in autonomous driving. Skills Appreciated - Experience with probabilistic models such as Gaussian mixture models, Hidden Markov Models, and Particle Filters. - Experience with machine learning techniques, including Bayesian modeling and inference for decision-making under uncertainty. - Experience with the Bazel build framework. Compensation and Benefits - Salary Range: $240,000—$330,000 USD (base salary). - Eligible for additional compensation such as bonus or company equity. - Benefits may include medical, dental, vision, 401k with company match, health savings accounts, life insurance, pet insurance, and more.

🏢 Summary: Machine Learning Engineer role focused on building and scaling ML-powered data mining pipelines for multimodal autonomous driving data, leveraging foundation models to discover rare edge cases and improve model performance. The position involves training and deploying models, developing embedding-based search and active learning workflows, and supporting production monitoring. You will collaborate across teams to translate ML prototypes into scalable, production-ready systems. 🗂️ Requirements: BS or MS in Computer Science, Machine Learning, or related field, Hands-on experience with PyTorch, TensorFlow, or JAX, Strong proficiency in Python, Experience with SQL and large-scale datasets, Proficiency with Pandas and NumPy, Knowledge of version control and unit testing, Understanding of full ML lifecycle from data preparation to deployment 📃 Skills: Python, PyTorch, TensorFlow, JAX, SQL, Pandas, NumPy, LiDAR, CI/CD, Git 🏢 Description: Mission Summary:At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery.As a Machine Learning Engineer on the Data Mining team, your mission is to help build the "Brain" of this engine. You will work with state-of-the-art foundation models to extract insights from Motional's driving data, working at the intersection of large-scale representation learning and data retrieval. By building smarter mining tools and efficient data pipelines, you will accelerate the model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation. What You'll Do: Build and Train ML Pipelines: Develop, train, and fine-tune machine learning models for multimodal sensor data (e.g., vision, LiDAR). Focus on implementing supervised and self-supervised learning approaches to improve data search and retrieval. Support Model Deployment: Implement scalable data preprocessing and augmentation pipelines. Assist in applying standard optimization techniques (e.g., batch inference, quantization) to ensure models run efficiently in production environments. Data Mining & Analysis: Help develop embedding-based search tools and "active learning" workflows to identify critical driving scenarios. Monitor Production Performance: Help build and maintain dashboards to monitor model health, data drift, and system performance. Identify regressions and assist in the operational support of our data mining services. Learn and Apply Best Practices: Follow software engineering standards (version control, CI/CD, unit testing) for ML code. Participate in code reviews and contribute to technical documentation. Collaborate Across Teams: Work closely with senior engineers and machine learning engineers to translate model prototypes into maintainable, scalable engineering solutions. What We're Looking For (Must-Haves): BS or MS in Computer Science, Machine Learning, or a related field. Hands-on experience with PyTorch (preferred) or TensorFlow/JAX. You should be comfortable training models and evaluating them using standard metrics. Strong proficiency in Python with the ability to write clean, modular, and well-documented code. Working knowledge of version control, unit testing, and basic software design patterns. Experience working with large datasets, including proficiency in SQL and data libraries like Pandas and NumPy. A solid grasp of the full ML lifecycle, from data cleaning and feature engineering to validation and deployment basics. A proactive learner who thrives on constructive feedback and is eager to grow within a high-stakes engineering environment. Bonus Points (Nice-to-Haves): MS/PhD in Computer Science, Machine Learning, or related field. Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning. Background in autonomous driving, robotics, or real-time decision-making systems. Familiarity with multimodal learning, sensor fusion, or embodied AI. Experience building active learning loops, using the model to find the data that breaks the model. Experience with ML-based data mining, active learning, or contrastive learning. Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms. Publication in top-tier conferences (e.g., ICCV, CVPR, ECCV) We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process. Candidates for certain positions are eligible to participate in Motional's benefits program. Motional's benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.Salary Range$144,000—$192,000 USDMotional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We're driven by something more. Our journey is always people first. We aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a technology with the potential to transform the way we move. Higher purpose, greater impact. We're creating first-of-its-kind technology that will transform transportation. To do so successfully, we must design for everyone in our cities and on our roads. We believe in building a great place to work through a progressive, global culture that is diverse, inclusive, and ensures people feel valued at every level of the organization. Diversity helps us to see the world differently; it's not only good for our business, it's the right thing to do. Scale up, not starting up. Our team is behind some of the industry's largest leaps forward, including the first fully-autonomous cross-country drive in the U.S, the launch of the world's first robotaxi pilot, and operation of the world's longest-standing public robotaxi fleet. We're driven to scale; we're moving towards commercialization of our technology, and we need team members who are ready to embrace change and challenges. Formed as a joint venture between Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives. Headquartered in Boston, Motional has operations in the U.S and Asia. For more information, visit www.Motional.com and follow us on Twitter, LinkedIn, Instagram and YouTube. Motional AD Inc. is an EOE. We celebrate diversity and are committed to creating an inclusive environment for all employees. To comply with Federal Law, we participate in E-Verify. All newly-hired employees are queried through this electronic system established by the DHS and the SSA to verify their identity and employment eligibility.

🏢 Summary: Senior technical leadership role responsible for defining and architecting large-scale machine learning systems that power multimodal data discovery and model improvement for autonomous driving. The position focuses on building scalable ML frameworks, optimizing real-time inference across GPU/CPU clusters, and leading cross-functional initiatives from roadmap to production. You will mentor engineers, set ML engineering standards, and drive department-level technical strategy. 🗂️ Requirements: BS in Computer Science, Machine Learning or related field, 8+ years of hands-on ML engineering experience, Proven ownership of architecture, deployment and optimization of large-scale ML systems, Experience with multimodal foundation models in production, Technical leadership in defining roadmaps and leading multi-person initiatives, Expert proficiency in Python, Strong experience with PyTorch, TensorFlow or JAX, Strong software engineering fundamentals (system design, CI/CD, containerization), Experience deploying ML models in AWS, GCP or Azure, Experience optimizing ML systems for latency, throughput and hardware efficiency 📃 Skills: Python, PyTorch, TensorFlow, JAX, AWS, GCP, Azure, CI/CD, Docker, Kubernetes, GPU, CPU, LiDAR, Radar 🏢 Description: Mission Summary: At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding rare edge cases, long-tail scenarios, and model errors. Omnitag, our ML-powered multimodal data mining framework, powers this discovery. As a Staff Machine Learning Engineer, you will define the roadmap and architecture for machine learning systems that power data discovery and model improvement lifecycles. You will architect scalable systems spanning multimodal representation learning, active learning loops, and optimized production inference. You will own system-level architecture, lead multi-quarter initiatives, and partner across engineering teams to influence technical strategy and ensure ML platforms serve as a mission-critical engine for the autonomy stack. What You'll Do: Define Technical Strategy & Roadmaps: - Develop and execute multi-quarter technical roadmaps for core ML systems - Guide reprioritization to drive team-wide and department-level OKRs and KPIs Architect System-Level Solutions: - Own system-level architecture for complex ML products - Design scalable frameworks for large-scale data mining and real-time inference across GPU/CPU clusters Drive Cross-Functional Execution: - Lead multi-person projects across teams - Influence partner teams' technical roadmaps and build alignment Elevate Engineering Excellence: - Establish standards for ML system design, code quality, testing, and deployment - Deliver processes to proactively address issues and participate in incident response planning Operate as a Generalist Expert: - Apply deep learning, representation learning, active learning, and generative AI to complex problems - Unblock teams facing unprecedented technical challenges Mentor and Lead: - Coach senior and junior engineers - Lead architectural reviews and contribute to engineering culture What We're Looking For (Must-Haves): - BS in Computer Science, Machine Learning, or related field (or equivalent experience) - 8+ years of hands-on ML engineering experience - Proven track record owning architecture, deployment, and optimization of large-scale ML systems - Experience with multimodal foundation models in production systems - Demonstrated technical leadership across multi-quarter initiatives - Expert proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX) - Strong software engineering fundamentals (system design, CI/CD, containerization) - Broad ML expertise across model training, deep learning architectures, evaluation, and production deployment - Experience deploying ML models in AWS, GCP, or Azure - Ability to mentor peers and drive consensus across teams Bonus Points: - MS or PhD in Computer Science, Machine Learning, or related field - Background in autonomous driving, robotics, or real-time decision systems - Experience with large-scale ML data mining and active learning loops - Familiarity with multimodal learning and sensor fusion - Experience with model serving tools (TF Serving, Triton, TorchServe) and enterprise MLOps platforms - Experience leading incident response planning for mission-critical ML platforms Benefits: - Hybrid or fully remote work options - Base salary range: $205,000—$272,500 USD - Eligibility for bonus or company equity - Medical, dental, vision coverage - 401k with company match - Health savings accounts - Life insurance - Pet insurance

🏢 Summary: Senior Machine Learning Engineer role focused on building and distilling large multimodal teacher models into efficient student models for large-scale autonomous vehicle data mining. The position emphasizes reinforcement learning, real-time inference optimization, and deployment of production-grade ML systems. You will design scalable training and deployment pipelines that accelerate data discovery and model improvement workflows. 🗂️ Requirements: BS in Computer Science, Machine Learning, or related field or equivalent experience, 6+ years of machine learning engineering experience, Hands-on experience with model distillation or teacher-student training, Experience with reinforcement learning including policy optimization and reward design, Expert proficiency in Python and at least one ML framework (PyTorch, TensorFlow, or JAX), Strong software engineering fundamentals including testing and CI/CD, Experience deploying ML models in cloud environments (AWS, GCP, or Azure), Proven track record of shipping production-grade ML systems 📃 Skills: Python, PyTorch, TensorFlow, JAX, PPO, DQN, Actor-Critic, ReinforcementLearning, KnowledgeDistillation, CI/CD, Docker, AWS, GCP, Azure, TFServing, Triton, TorchServe 🏢 Description: Mission Summary: At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery. As a Senior Machine Learning Engineer on the Data Mining team, your mission is to build the "Brain" of this engine: designing massive multimodal Teacher models that understand the world, and distilling them into hyper-efficient Student models that can scour exabytes of data in near real-time. You will work at the intersection of large-scale representation learning, retrieval optimization, and reasoning systems. Your work will directly influence how we compress knowledge into efficient encoders for fast search, and how we apply reinforcement learning to optimize data discovery workflows and intelligent querying. By building smarter mining tools, you will accelerate the entire model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation. What You'll Do: - Architect and Train Distilled Models: Design and implement teacher-student model frameworks for multimodal sensor data. Develop training pipelines for knowledge distillation. Ensure student models maintain high accuracy while drastically reducing inference latency and memory footprint. - Reinforcement Learning for Data Discover: Build RL-based policy learning and reasoning systems for autonomous driving applications. Implement and scale RL training workflows (e.g., PPO, DQN, actor-critic methods) for simulation and real-world interaction. Explore reward shaping, environment modeling, and multi-agent RL where applicable. - Optimize Model Deployment for Real-Time Inference: Collaborate with backend engineers to deploy distilled and RL models into production. Optimize for latency, throughput, and hardware efficiency across GPU/CPU clusters. Implement model versioning, A/B testing, and monitoring for performance regressions. - Research and Integrate Agentic Systems: Explore and prototype agentic workflows for autonomous reasoning, chain-of-thought prompting, and goal-directed behavior. Integrate such systems into our broader autonomy stack as experimental or production components. - Drive Production Reliability: Establish patterns for graceful degradation, fault tolerance, and cost optimization. Operate Omnitag as a mission-critical data platform serving the entire ML organization, with a focus on reliability, debuggability, and operational excellence. - Mentor and Collaborate: Work closely with ML scientists, data engineers, and autonomy teams to translate research advances into scalable engineering solutions. Guide junior engineers in best practices for model training, evaluation, and deployment. What We're Looking For: - BS in Computer Science, Machine Learning, or related field, or equivalent professional experience. - 6+ years of hands-on experience in machine learning engineering, with a focus on model post training, optimization, and deployment. - Strong experience with model distillation or teacher-student training - practical knowledge of loss functions, training strategies, and evaluation of compressed models. - Proven experience with reinforcement learning in production or research settings: policy optimization, reward design, simulation environments, and RL-based reasoning. - Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX). - Strong software engineering fundamentals: testing, CI/CD, containerization, and system design. - Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for inference. - Demonstrated ability to ship production-grade ML systems and mentor team members. - Demonstrated track record of shipping robust, well-tested, production-grade systems and mentoring junior engineers. Bonus Points (Nice-to-Haves): - MS/PhD in Computer Science, Machine Learning, or related field. - Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning. - Background in autonomous driving, robotics, or real-time decision-making systems. - Familiarity with multimodal learning, sensor fusion, or embodied AI. - Experience building active learning loops, using the model to find the data that breaks the model. - Experience with ML-based data mining, active learning, or contrastive learning. - Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms. - Publications or open-source contributions in RL, distillation, or efficient ML. We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote. The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. Candidates for certain positions are eligible to participate in Motional's benefits program. Motional's benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more. Salary Range $172,000—$229,000 USD

🏢 Summary: Software engineering role focused on designing and developing high‑performance embedded infrastructure for onboard autonomous driving systems across diverse hardware platforms. The position involves building and testing embedded software for vision, radar, and safety applications, leading technical initiatives, and collaborating cross‑functionally. Opportunities are available from graduate to staff level, with hybrid or remote work options. 🗂️ Requirements: Experience creating detailed requirements from use cases, Ability to lead technical initiatives and guide engineers, Experience developing embedded software in C, Experience developing embedded software in C++, Experience with Test-Driven Development (TDD), Experience with embedded Linux or RTOS, Experience with networking (Ethernet, CAN) and protocols, Experience debugging on embedded platforms, Experience programming in Python, Experience with shell scripting for automation, Experience working with ARM Cortex MCUs or microprocessors 📃 Skills: C, C++, Python, Shell, Linux, RTOS, Ethernet, CAN, ARM, TDD, Debugging, Networking 🏢 Description: Mission Summary: Motional's onboard autonomous driving system team works at the intersection of software engineering, machine learning, sensors, and hardware compute platforms to evolve next-generation onboard autonomous driving systems. The High Performance Compute Platform team is responsible for current and next-generation onboard autonomous driving systems. Hiring spans graduate to Staff engineer levels. What You'll Be Doing: - Design and develop infrastructure software on various hardware platforms for applications such as vision processing, radar systems, and safety monitoring to run on self-driving vehicles. - Design test harnesses for embedded software components and full systems. - Provide technical mentorship to engineers. - Work with cross-functional engineering teams to solve complex technical problems. What We're Looking For: - Experience creating detailed requirements from use cases. - Ability to lead technical initiatives, break down work, and guide engineers through execution. - Experience writing software for embedded platforms in C and C++. - Experience with Test-Driven Development (TDD). - Experience working on embedded Linux or RTOS. - Experience with networking (Ethernet, CAN) and common networking protocols. - Experience debugging on embedded platforms. - Experience writing software in Python and automating with shell scripting. - Experience working with ARM Cortex MCUs or microprocessors. Bonus Points (not required): - Experience with large data pipelines and deterministic execution platforms. - Experience with inter-system communication protocols such as I2C and SPI. - Experience deploying Machine Learning models. - Experience working with GPUs. - Experience working with the Linux kernel or device drivers. - Experience with simulation and code generation. - Experience working with Bazel. - Experience integrating sensors including cameras, IMUs, radars, and LIDARs. - Experience with PyTorch, TensorFlow, ONNX, or other ML frameworks. Work Arrangement: Hybrid schedule with in-office time in Boston, Pittsburgh, or Las Vegas, or fully remote. Compensation & Benefits: Salary Range: $149,000—$198,500 USD (base salary). Additional compensation may include bonus or company equity. Benefits may include medical, dental, vision, 401k with company match, health savings accounts, life insurance, pet insurance, and more.