Senior DevSecOps Engineer

🏢 Summary: Staff Software Engineer role leading development of operational tools for a commercial Autonomous Vehicle ride service, acting as the key technical bridge between Operations and global Engineering. The position focuses on building scalable fleet management and orchestration systems while providing hands-on production support. Based in Las Vegas, it combines distributed systems design, product thinking, and stakeholder alignment. 🗂️ Requirements: 8+ years professional software engineering experience, Proven experience designing and building distributed systems, Strong product mindset with ability to translate operational needs into technical solutions, Experience supporting production systems, Ability to manage stakeholders and collaborate with remote engineering teams, Proficiency in Golang or Python, Experience building cloud services with SQL and NoSQL databases, Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience) 📃 Skills: Golang, Python, SQL, NoSQL, AWS, Docker, Terraform, ClickHouse, OLAP 🏢 Description: Mission Summary: Join as a key technical leader in Las Vegas to launch a commercial Autonomous Vehicle (AV) ride service. The role focuses on bridging Operations and the global Engineering team by leading development of critical operational tools such as fleet management and orchestration systems, ensuring technology meets real-world needs. What You'll Be Doing: Hands-on Development & Leadership - Build High-Impact Ops Tools: Lead the coding and delivery of frontend and backend services used daily by Operations to monitor and manage the fleet, balancing long-term scalability with immediate operational needs. - Act as the primary engineering presence at the Las Vegas AV operation center, providing real-time technical support and troubleshooting. - Interview and onboard new hires, mentor junior engineers, and define workflows (handovers, async communication, documentation standards) to enable collaboration between Las Vegas and Singapore. Product Engineering & Stakeholder Alignment - Own the "Ops-to-Tech" Bridge: Partner with Operations, Product, and TPMs to translate real-world fleet challenges into actionable technical requirements for the global engineering team. - Shape the Tooling Roadmap: Drive the vision for fleet management and orchestration systems, identifying impactful problems to improve fleet efficiency and reduce manual work. - Feedback Loop Architect: Design processes and features that convert operational feedback into quantitative data to prioritize platform improvements. What We're Looking For: - 8+ years of professional experience as a software engineer with a track record of designing and building distributed systems. - Strong product mindset focused on delivering operational value. - Experience supporting production systems with strong communication skills. - Ability to manage stakeholders and collaborate effectively with remote teams. - Proficiency in Golang or Python for web services and scripting. - Experience building cloud services using SQL and NoSQL databases. - Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent practical experience). Bonus Points (not required): - Experience with Amazon Web Services (AWS), Docker, and Terraform. - Experience with OLAP databases (e.g., ClickHouse) or building observability tools for monitoring and tracing. - Experience in Autonomous Vehicle (AV), Robotics, or IoT industries. Compensation & Benefits: Salary Range: $172,000—$229,000 USD (base salary). This role may include 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 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: 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 DevOps Engineer role focused on designing, automating, and operating AWS-based cloud infrastructure for a large-scale data and AI platform. The position centers on Infrastructure as Code, platform reliability, and enabling secure, scalable analytics workloads using Databricks and Amazon Athena. You will work hands-on with cloud and DevOps technologies in a cross-functional data environment. 🗂️ Requirements: Experience as DevOps Engineer in production cloud environments, Strong hands-on experience with AWS services, Practical experience with Databricks in cloud environments, Experience designing and managing infrastructure with Terraform, Hands-on experience with Amazon Athena, Experience with CI/CD pipelines, Experience with Git-based workflows, Knowledge of Docker and Kubernetes, Experience working with data or analytics platforms, Professional proficiency in French, Professional working proficiency in English 📃 Skills: AWS, Databricks, Terraform, Athena, Docker, Kubernetes, Airflow, MLflow, CI/CD, Git, Python, Shell, Monitoring, Logging, Cloud 🏢 Description: Client The world’s largest sporting goods retailer, with a global team of 5,000+ experts across engineering, product, data, cloud, and cybersecurity, is building the largest digital sports platform—driving innovation from product design to customer experience and sustainability. Project overview The project focuses on a cloud-native data platform supporting large-scale analytics, AI, and data processing workloads.The platform leverages technologies such as Databricks and Amazon Athena, ensuring high standards for automation, scalability, security, and operational excellence. Team You will work in a cross functional team that includes DevOps engineers, data engineers, software developers, and product stakeholders. The team collaborates closely, sharing responsibility for infrastructure quality, deployment pipelines, and platform stability. Position overview We are looking for a Senior DevOps Engineer to design, automate, and operate cloud infrastructure supporting data and AI workloads. You will focus on infrastructure automation, platform reliability, and enabling data workloads to run securely and efficiently in the cloud. The role combines hands on technical work with close collaboration across engineering and data teams. Technology stack AWS, Databricks, Terraform, AWS Cloud services, Amazon Athena, Docker, Kubernetes, Airflow, MLflow, CI CD pipelines, Git based workflows, monitoring and logging tools, scripting languages Responsibilities Design, implement, and maintain cloud infrastructure on AWS using Infrastructure as Code practices Build and manage Terraform based infrastructure to support data and analytics workloads Support and optimize Databricks environments running on AWS Configure and manage Amazon Athena for querying and analytics use cases Develop, maintain, and improve CI CD pipelines for infrastructure and platform components Monitor platform performance, availability, and security and address operational issues Collaborate with data engineers and developers to translate platform requirements into technical solutions Troubleshoot infrastructure and deployment issues and perform root cause analysis Contribute to platform standardization, documentation, and continuous improvement initiatives Requirements Experience working as a DevOps Engineer in production cloud environments Strong hands on experience with AWS services Practical experience using Databricks in a cloud based environment Experience designing and managing infrastructure with Terraform Hands on experience with Amazon Athena Experience working with CI CD pipelines and Git based workflows Knowledge of containerization (Docker, Kubernetes) Experience working in data or analytics platforms Ability to communicate effectively in French in a professional context Professional working proficiency in English Nice to have Experience with data engineering or analytics platforms Exposure to multi-cloud architectures (AWS & GCP) Experience in enterprise-scale environments Strong interest in AI / Generative AI technologies Scripting or programming experience with Python, Shell, or similar languages Experience working in large scale or enterprise environments What We Offer: Vacation days : Up to 26 business days per year. 10 illness/special days off per year (fully paid, no medical papers needed) for all contract types Health and life insurance (Luxmed) MyBenefit platform with Multisport option Internal psychological support service English language classes from the first working day Access to external learning platforms : O’Reilly, LinkedIn Learning, Udemy, and a wide catalog of diverse internal training Flexible workplace : work from the office, from home, or choose a hybrid option Tech Skills Mentoring Program Opportunities to develop as a public speaker, mentor, or technical interviewer Fully paid idle (bench) when not involved in a project Certification reimbursement (AWS, GCP, Microsoft, etc.)