Principal Engineer Team Lead, Prediction & ML Planner

🏢 Summary: Lead the design and deployment of advanced motion planning and prediction models for Level 4 autonomous vehicles, leveraging machine learning, generative AI, and reinforcement learning. The role focuses on improving safety and performance in complex traffic scenarios while collaborating across perception, simulation, and integration teams. This position combines technical leadership with hands-on development and production deployment on vehicle fleets. 🗂️ Requirements: Master’s or Ph.D. in Computer Science or related technical field or equivalent industry experience, Proven leadership in executing large, complex technical initiatives, Experience designing, developing, and deploying ML solutions for autonomous vehicles or robotics, Experience with deep learning frameworks such as TensorFlow or PyTorch, Fluency in Python and scientific computing libraries, 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, Optimization 🏢 Description: What You'll Be Doing: - Define and execute motion planning and prediction projects that improve self-driving vehicles' capability to safely, comfortably and legally navigate complex traffic scenarios - Design and lead the implementation of behavior models that leverage the latest 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 at executing large, complex technical initiatives - 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, 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 - Proven track record of publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, ICL, etc.) - Strong programming skills in C++ and/or CUDA programming Compensation and Benefits: Salary Range: $240,000—$330,000 USD. The salary range reflects base salary only and may vary based on skills, experience, location, certifications, and business needs. Additional compensation may include bonus or company equity. Eligible positions include participation in a benefits program that includes medical, dental, vision, 401k with company match, health savings accounts, life insurance, pet insurance, and more.

🏢 Summary: Distinguished Machine Learning Engineer role within the Autonomy Behaviors team focused on developing and deploying deep learning solutions for prediction, planning, and control in autonomous vehicles. The position involves leading large-scale ML experimentation, building production-grade models, and collaborating cross-functionally to deliver industrial-strength systems. Candidates must bring extensive experience in autonomous vehicle ML systems, deep neural networks, and large-scale model deployment. 🗂️ 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 similar robotics applications, Deep understanding of large language models (LLM) and transformers, Hands-on experience building and deploying large-scale production ML systems, Experience training, optimizing, and deploying deep neural networks in PyTorch, TensorFlow, or TensorRT, Strong mathematical foundation in machine learning and deep learning, Proven leadership and innovation in ML-based planning solutions 📃 Skills: Python, MachineLearning, DeepLearning, LLM, Transformers, DNN, PyTorch, TensorFlow, TensorRT, Prediction, Planning, Control, Optimization 🏢 Description: Motional is seeking a distinguished Machine Learning Engineer to join its Autonomy team in Behaviors. As a member of our team you will develop key features for our autonomous driving platform. In this role, you will apply machine learning to a mix of prediction, planning, and control problems. The candidate is required to have hands-on experience and deep knowledge in machine learning. Understanding of deep neural networks, autonomous vehicles, and domain adaptation is highly desirable. You should have strong research, SW development, communication, interpersonal, and analytical skills. 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 Salary Range $271,000—$373,000 USD 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 reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. Benefits: Candidates for certain positions are eligible to participate in the benefits program, including but not limited to medical, dental, vision, 401k with a company match, health saving 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: Develop and implement advanced motion planning algorithms for production-ready autonomous vehicles, focusing on safe and intuitive route generation. The role combines robotics research and C++ software development, integrating planning with perception, prediction, and control systems. You will contribute to scalable codebases and bring motion planning solutions from concept to deployment. 🗂️ Requirements: Bachelor’s degree in Robotics, Computer Science, Computer Engineering, Mechanical Engineering or related field, 2+ years of research experience in robotics or motion planning, 2+ years of C++ software development experience, Proven experience in robotics or autonomous vehicles, Experience delivering projects from problem formulation to deployment 📃 Skills: C++, Robotics, MotionPlanning, AutonomousVehicles, Algorithms, Optimization, LinearTemporalLogic, DecisionMaking, SoftwareDevelopment 🏢 Description: Role Responsibilities: - Develop a variety of algorithms on planning for autonomous driving, including but not limited to search-based methods, sampling-based methods, optimization-based methods, linear-temporal logic, and decision making under uncertainty. - Integrate and evaluate combinations of motion planning and prediction algorithms. - Design and build robust and scalable codebase that enables rapid exploration and evaluation of different motion planning approaches and algorithms. - Interface with perception and prediction components upstream and trajectory optimization and tracking & control components downstream. - Participate in code reviews and mentoring sessions with senior team members. - Develop a culture of product focused engineering, research, and development. What We're Looking For: - Bachelor's required, Masters or PhD degree preferred in Robotics, Computer Science, Computer Engineering, Mechanical Engineering, or related field. - Proven impact and expertise in the robotics / autonomous vehicle field. - 2+ years of research experience in robotics / motion planning. - 2+ years of C++ software development. - Past experience taking projects from problem formulation through implementation and deployment. - Thirst for knowledge and continuous innovation. Compensation and Benefits: - Minimum salary of $172,020/year + bonus + equity + benefits (Colorado only). - Salary range: $240,000—$330,000 USD. - Eligible to participate in benefits 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: 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: Senior technical role leading research, architecture, and development of advanced motion planning and control systems for production autonomous vehicles. The position focuses on designing probabilistic, search-based, and geometry-based algorithms, integrating them into high-performance C++ systems, and driving end-to-end deployment in complex real-world environments. It involves cross-functional leadership, system optimization, and mentorship within a robotics-focused engineering team. 🗂️ 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++ development experience, Proven experience leading complex technical features from research to production deployment, Experience developing high-performance, reliable software systems, Strong background in motion planning and decision-making under uncertainty, Ability to lead cross-functional technical projects 📃 Skills: C++, Robotics, MotionPlanning, Algorithms, ProbabilisticModels, GaussianMixtureModels, HiddenMarkovModels, ParticleFilters, MachineLearning, BayesianInference, Bazel, TrajectoryOptimization, ControlSystems 🏢 Description: Role Responsibilities: Lead the research and development of novel algorithms and sub-systems for motion planning in autonomous driving, expanding the Operational Design Domain. This includes advanced search-based and geometry-based methods, as well as decision-making under uncertainty with a strong emphasis on probabilistic approaches. Lead cross-functional projects to define new or upgrade existing interfaces to solve problems. Monitor overall system performance to identify areas for improvement and develop technical strategies to address deficiencies. Guide cross-functional project teams to provide comprehensive solutions and think beyond the confines of the planning system. Architect and integrate complex combinations of motion planning and prediction algorithms, driving their evaluation and refinement for real-world deployment. Design and build a robust, scalable, and high-performance codebase that facilitates rapid exploration, prototyping, and rigorous evaluation of innovative motion planning approaches and algorithms. Drive technical collaboration and interface with perception and prediction components upstream and trajectory optimization, tracking, and control components downstream to ensure end-to-end system performance. Leverage deep software development and research expertise to teach better software practices and principles. Guide and mentor junior and senior team members, cultivating a culture of product-focused engineering, rigorous research, and advanced development. What We're Looking For: PhD preferred in Robotics, Computer Science, Computer Engineering, Mechanical Engineering, or a related field; or a Master’s degree with 7+ years of experience in robotics (preferably autonomous vehicles industry). 10+ years of research experience in robotics or motion planning, with a proven track record of contributing to state-of-the-art solutions and leading significant projects. 5+ years of C++ software development experience, focused on high-performance and reliable systems. Experience owning and leading technical development of complex features from problem formulation through research, implementation, and deployment in production environments. Strong drive for innovation and advancement in autonomous driving technology. Skills Appreciated: Experience with probabilistic models, including Gaussian mixture models, Hidden Markov Models, and Particle Filters. Experience with machine learning techniques such as 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). This role may include additional compensation such as bonus or company equity. Eligible positions include benefits such as medical, dental, vision, 401k with company match, health savings accounts, life insurance, pet insurance, and more.

🏢 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-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: Staff Machine Learning Engineer role focused on architecting and leading large-scale ML systems that power multimodal data discovery and model improvement for autonomous driving. The position owns system-level architecture, technical strategy, and cross-functional execution across massive data mining and real-time inference platforms. It combines deep hands-on ML expertise with technical leadership and mentorship at department scale. 🗂️ 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), Technical leadership experience defining multi-quarter roadmaps and leading multi-person initiatives, Expert proficiency in Python and at least one major ML framework (PyTorch, TensorFlow, or JAX), Strong software engineering fundamentals (system design, CI/CD, containerization), Broad ML expertise across model training, deep learning, evaluation, and large-scale deployment, Experience deploying ML models in cloud environments (AWS, GCP, or Azure), Ability to mentor engineers and drive cross-team technical alignment 📃 Skills: Python, PyTorch, TensorFlow, JAX, AWS, GCP, Azure, CI/CD, Containerization, DeepLearning, RepresentationLearning, ActiveLearning, GenerativeAI, MultimodalModels, ModelServing, MLOps, GPU, CPU 🏢 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 that matter most. Omnitag, our ML-powered multimodal data mining framework, powers this discovery. As a Staff Machine Learning Engineer, you will serve as a technical leader defining 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 high-efficiency production inference. You will own system-level architecture, lead multi-quarter initiatives, and partner across engineering to influence department-wide technical strategy while establishing robust processes and mentoring others. What You'll Do: - Define Technical Strategy & Roadmaps: Develop and execute multi-quarter, high-impact technical roadmaps for core ML systems, aligning with team and department OKRs and KPIs. - Architect System-Level Solutions: Own architecture for complex ML products and 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 and influence partner roadmaps to solve shared technical challenges. - Elevate Engineering Excellence: Establish standards for ML system design, code quality, testing, deployment, and incident response planning. - Operate as a Generalist Expert: Apply deep learning, representation learning, active learning, and generative AI to complex problems and unblock teams facing novel challenges. - Mentor and Lead: Coach engineers, lead architectural reviews, and contribute to engineering culture through documentation and technical 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, multi-person initiatives - Expert proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX) - Strong software engineering fundamentals including system design, CI/CD, and containerization - Broad ML experience across training, architectures, evaluation, and large-scale deployment - Experience deploying ML models in cloud environments (AWS, GCP, or Azure) with latency and throughput optimization - Proven mentorship and cross-team collaboration skills Bonus Points (Nice-to-Haves): - 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 contrastive/representation learning - Familiarity with multimodal learning, sensor fusion, or large foundation models - Experience with model serving tools (TF Serving, Triton, TorchServe) and enterprise MLOps platforms - Experience leading severity reviews or incident response planning for mission-critical ML platforms Work Arrangement & Compensation: - Hybrid schedule with in-office collaboration in Boston, Pittsburgh, or Las Vegas, or fully remote - Base salary range: $205,000—$272,500 USD - 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