Principal Engineer Tech Lead Manager, ML Acceleration

🏢 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: 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

🏢 Summary: Staff Machine Learning Engineer role focused on architecting and leading large-scale, production-grade ML systems for multimodal data mining and model improvement in autonomous driving. The position drives technical strategy, system-level design, and deployment of scalable ML frameworks across GPU/CPU clusters. It combines deep ML expertise with technical leadership to build mission-critical platforms for data discovery and real-time inference. 🗂️ Requirements: BS in Computer Science, Machine Learning, or related field, 8+ years of ML engineering experience, Proven ownership of architecture, deployment, and optimization of large-scale ML systems, Experience with multimodal foundation models in production systems, 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 across model training, deep learning, evaluation, and production deployment, 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, DeepLearning, ActiveLearning, MLOps 🏢 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 our department-wide technical strategy. By establishing robust processes and mentoring those around you, you will ensure our ML platforms act as a reliable, mission-critical engine for the entire autonomy stack. What You'll Do: Define Technical Strategy & Roadmaps: Develop and execute multi-quarter, high-impact technical roadmaps for core ML systems. Proactively inform leadership to guide reprioritization, ensuring initiatives consistently drive team-wide and department-level OKRs and KPIs. Architect System-Level Solutions: Own the system-level architecture for complex ML products. Design scalable frameworks for massive data mining and highly optimized, real-time inference across GPU/CPU clusters. Drive Cross-Functional Execution: Lead multi-person projects to completion across teams. Influence partner teams' technical roadmaps (such as Autonomy) to solve shared problems, break down silos, and build alignment. Elevate Engineering Excellence: Establish department-wide standards for ML system design, code quality, testing, and deployment. Deliver processes to proactively address issues and participate in org-wide incident response planning. Operate as a Generalist Expert: Apply a broad toolkit of ML techniques (deep learning, representation learning, active learning, generative AI) to solve complex, ambiguous problems. Unblock yourself and your team when facing unprecedented technical challenges. Mentor and Lead: Act as a role model and technical go-to person. Coach Senior and junior engineers, lead architectural reviews, and elevate Motional's engineering culture through internal documentation, tech talks, and collaborative design. What We're Looking For (Must-Haves): BS in Computer Science, Machine Learning, or a related field (or equivalent practical experience) 8+ years of hands-on ML engineering experience, with a proven track record of owning architecture, deployment, and optimization of large-scale ML systems Demonstrated experience working with multimodal foundation models in ML production systems, including integration, scaling, fine-tuning, or deployment of models that process multiple data modalities (e.g., camera, LiDAR, radar, text) Demonstrated technical leadership: defining multi-quarter roadmaps, leading multi-person initiatives, and driving department-level technical strategy Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX), backed by strong software engineering fundamentals (system design, CI/CD, containerization) Broad ML generalist knowledge, with practical experience spanning model training, deep learning architectures, evaluation methodologies, and production deployment at scale Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for latency, throughput, and hardware efficiency Proven ability to mentor peers, explain complex trade-offs to leadership, and drive consensus across disparate teams Bonus Points (Nice-to-Haves): MS/PhD in Computer Science, Machine Learning, or a related field. Background in autonomous driving, robotics, or complex real-time decision-making systems. Experience with massive-scale ML data mining, active learning loops, and contrastive/representation learning. Familiarity with multimodal learning, sensor fusion, or large foundation models. Deep knowledge of model serving tools (TF Serving, Triton, TorchServe) and enterprise MLOps platforms. Demonstrated experience leading org-wide severity reviews or establishing incident response planning for mission-critical ML platforms. 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$205,000—$272,500 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: Staff Machine Learning Engineer role focused on architecting and leading large-scale, multimodal ML systems for autonomous vehicle data mining and model improvement. The position drives technical strategy, system-level architecture, and production deployment of scalable training and inference pipelines across GPU/CPU clusters. It combines hands-on ML expertise with technical leadership to build robust, mission-critical ML platforms. 🗂️ 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, Expert proficiency in Python, Expert proficiency in at least one ML framework: PyTorch, TensorFlow, or JAX, Strong software engineering fundamentals: system design, CI/CD, containerization, Experience across model training, deep learning architectures, evaluation, and production deployment, Experience deploying ML systems in AWS, GCP, or Azure, Experience optimizing ML systems for latency, throughput, and hardware efficiency, Demonstrated technical leadership in multi-person, multi-quarter initiatives 📃 Skills: Python, PyTorch, TensorFlow, JAX, AWS, GCP, Azure, CI/CD, Docker, Kubernetes, GPU, CPU, DeepLearning, RepresentationLearning, ActiveLearning, GenerativeAI, MLOps 🏢 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 our department-wide technical strategy. By establishing robust processes and mentoring those around you, you will ensure our ML platforms act as a reliable, mission-critical engine for the entire autonomy stack. What You'll Do: Define Technical Strategy & Roadmaps: Develop and execute multi-quarter, high-impact technical roadmaps for core ML systems. Proactively inform leadership to guide reprioritization, ensuring initiatives consistently drive team-wide and department-level OKRs and KPIs. Architect System-Level Solutions: Own the system-level architecture for complex ML products. Design scalable frameworks for massive data mining and highly optimized, real-time inference across GPU/CPU clusters. Drive Cross-Functional Execution: Lead multi-person projects to completion across teams. Influence partner teams' technical roadmaps (such as Autonomy) to solve shared problems, break down silos, and build alignment. Elevate Engineering Excellence: Establish department-wide standards for ML system design, code quality, testing, and deployment. Deliver processes to proactively address issues and participate in org-wide incident response planning. Operate as a Generalist Expert: Apply a broad toolkit of ML techniques (deep learning, representation learning, active learning, generative AI) to solve complex, ambiguous problems. Unblock yourself and your team when facing unprecedented technical challenges. Mentor and Lead: Act as a role model and technical go-to person. Coach Senior and junior engineers, lead architectural reviews, and elevate Motional's engineering culture through internal documentation, tech talks, and collaborative design. What We're Looking For (Must-Haves): BS in Computer Science, Machine Learning, or a related field (or equivalent practical experience) 8+ years of hands-on ML engineering experience, with a proven track record of owning architecture, deployment, and optimization of large-scale ML systems Demonstrated experience working with multimodal foundation models in ML production systems, including integration, scaling, fine-tuning, or deployment of models that process multiple data modalities (e.g., camera, LiDAR, radar, text) Demonstrated technical leadership: defining multi-quarter roadmaps, leading multi-person initiatives, and driving department-level technical strategy Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX), backed by strong software engineering fundamentals (system design, CI/CD, containerization) Broad ML generalist knowledge, with practical experience spanning model training, deep learning architectures, evaluation methodologies, and production deployment at scale Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for latency, throughput, and hardware efficiency Proven ability to mentor peers, explain complex trade-offs to leadership, and drive consensus across disparate teams Bonus Points (Nice-to-Haves): MS/PhD in Computer Science, Machine Learning, or a related field. Background in autonomous driving, robotics, or complex real-time decision-making systems. Experience with massive-scale ML data mining, active learning loops, and contrastive/representation learning. Familiarity with multimodal learning, sensor fusion, or large foundation models. Deep knowledge of model serving tools (TF Serving, Triton, TorchServe) and enterprise MLOps platforms. Demonstrated experience leading org-wide severity reviews or establishing incident response planning for mission-critical ML platforms. 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$205,000—$272,500 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: Staff Machine Learning Engineer role focused on architecting and leading large-scale, production-grade ML systems that power multimodal data mining and model improvement for autonomous driving. The position centers on defining technical strategy, building scalable ML infrastructure, and optimizing real-time inference across distributed environments. It combines hands-on ML system design with cross-functional 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 experience architecting, deploying and optimizing large-scale ML systems, Experience with multimodal foundation models in production, Expert-level proficiency in Python, Strong experience with PyTorch, TensorFlow or JAX, Strong software engineering fundamentals including system design, CI/CD and containerization, Experience deploying ML models in cloud environments such as AWS, GCP or Azure, Experience optimizing ML systems for latency, throughput and hardware efficiency, Broad experience across model training, deep learning architectures, evaluation and production deployment, Demonstrated technical leadership in defining roadmaps and leading multi-person initiatives 📃 Skills: Python, PyTorch, TensorFlow, JAX, AWS, GCP, Azure, CI/CD, Docker, Kubernetes, GPU, CPU, DeepLearning, ActiveLearning, GenerativeAI, MultimodalLearning, ModelServing, SystemDesign 🏢 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 our department-wide technical strategy. By establishing robust processes and mentoring those around you, you will ensure our ML platforms act as a reliable, mission-critical engine for the entire autonomy stack. What You'll Do: Define Technical Strategy & Roadmaps: Develop and execute multi-quarter, high-impact technical roadmaps for core ML systems. Proactively inform leadership to guide reprioritization, ensuring initiatives consistently drive team-wide and department-level OKRs and KPIs. Architect System-Level Solutions: Own the system-level architecture for complex ML products. Design scalable frameworks for massive data mining and highly optimized, real-time inference across GPU/CPU clusters. Drive Cross-Functional Execution: Lead multi-person projects to completion across teams. Influence partner teams' technical roadmaps (such as Autonomy) to solve shared problems, break down silos, and build alignment. Elevate Engineering Excellence: Establish department-wide standards for ML system design, code quality, testing, and deployment. Deliver processes to proactively address issues and participate in org-wide incident response planning. Operate as a Generalist Expert: Apply a broad toolkit of ML techniques (deep learning, representation learning, active learning, generative AI) to solve complex, ambiguous problems. Unblock yourself and your team when facing unprecedented technical challenges. Mentor and Lead: Act as a role model and technical go-to person. Coach Senior and junior engineers, lead architectural reviews, and elevate Motional's engineering culture through internal documentation, tech talks, and collaborative design. What We're Looking For (Must-Haves): BS in Computer Science, Machine Learning, or a related field (or equivalent practical experience) 8+ years of hands-on ML engineering experience, with a proven track record of owning architecture, deployment, and optimization of large-scale ML systems Demonstrated experience working with multimodal foundation models in ML production systems, including integration, scaling, fine-tuning, or deployment of models that process multiple data modalities (e.g., camera, LiDAR, radar, text) Demonstrated technical leadership: defining multi-quarter roadmaps, leading multi-person initiatives, and driving department-level technical strategy Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX), backed by strong software engineering fundamentals (system design, CI/CD, containerization) Broad ML generalist knowledge, with practical experience spanning model training, deep learning architectures, evaluation methodologies, and production deployment at scale Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for latency, throughput, and hardware efficiency Proven ability to mentor peers, explain complex trade-offs to leadership, and drive consensus across disparate teams Bonus Points (Nice-to-Haves): MS/PhD in Computer Science, Machine Learning, or a related field. Background in autonomous driving, robotics, or complex real-time decision-making systems. Experience with massive-scale ML data mining, active learning loops, and contrastive/representation learning. Familiarity with multimodal learning, sensor fusion, or large foundation models. Deep knowledge of model serving tools (TF Serving, Triton, TorchServe) and enterprise MLOps platforms. Demonstrated experience leading org-wide severity reviews or establishing incident response planning for mission-critical ML platforms. 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$205,000—$272,500 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: 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: 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.