Jobs at Motional

Lead design and build of internal web visualization tooling for ML and AV teams. Architect scalable React/TypeScript/Vue frontends, collaborate cross-functionally, drive performance and UX best practices, mentor engineers, and deliver mission-critical data-heavy UI systems.

Lead commercialization of autonomous vehicle services from pilot to scaled fleet over a 1–3 year horizon. Drive GTM execution, build commercial models, harvest deployment insights, translate requirements to Product and Engineering, coordinate cross-functional launches, and create repeatable playbooks to improve unit economics and user experience.

Design and build large-scale mining solutions to find challenging driving scenarios, improve learned model performance, and support continuous learning. Collaborate with ML infrastructure to enable iterative mining, error analysis, training and deployment. Research uncertainty and informativeness metrics, run deep learning experiments, provide statistical insight on model uncertainty and robustness, write technical reports, and mentor junior researchers.

The Senior Technical Program Manager will oversee software performance evaluations, manage resources, and coordinate between engineering teams to ensure quality metrics are met while addressing risks and issues.

Develop and integrate motion-planning and decision-making algorithms for autonomous driving. Build robust, scalable C++ code and CI/CD pipelines, process and analyze vehicle field data, optimize large data pipelines, lead feature development, and mentor junior engineers.

Design, implement, and test onboard and offboard localization software pipelines for autonomous vehicles. Develop sensor processing, fusion, and SLAM for deployment, perform code reviews, mentor junior engineers, and coordinate APIs with mapping and cross-functional teams (perception, planning, controls).

Lead the development of the ML Data Service platform, manage engineers, drive technical strategy, and ensure high-quality data for ML use cases.

Lead multiple machine learning teams focusing on prediction and planning for autonomous vehicles, setting technical direction, and fostering organizational growth through innovative AI solutions.

As a Machine Learning Systems Engineer, you will optimize distributed training systems, enhance performance profiling, and develop high-performance GPUs for machine learning workloads.

Lead improvements to decision-making, motion planning, and controls software quality for driverless vehicles. Implement validation, diagnostics, static analysis, compiler optimizations, and eliminate runtime allocations. Develop and deploy agentic AI tools to enforce design and validation principles, collaborate across subsystems, and present results to reduce failures before commercial launch.

Lead the research and development of algorithms for motion planning in autonomous driving, integrating predictive systems and mentoring team members.

Lead large, cross-functional technical programs for autonomy, owning model development and release cycles. Act as DRI for behavioral capabilities, integrate Prediction and ML Planning, dig into ML/behavior issues, identify and mitigate technical risks, and align roadmaps with engineering, product, and executive stakeholders to deliver driverless milestones.

Technical leader owning motion planning and trajectory optimization for production autonomous vehicles. Architect scalable C++ systems, integrate optimal-control solvers, define testing/simulation/CI tooling, lead cross-functional design, and mentor engineers to deliver safe, real-time on-vehicle implementations.

The role involves developing perception components for self-driving vehicles, analyzing system performance, and collaborating with cross-functional teams to enhance technology.

Lead and grow an AI Data Application team to build web services and platforms for metadata storage, dataset generation, and data search. Define technical vision, drive AI adoption in frontend UX, design APIs and query federation, collaborate with ML researchers and data teams, and mentor engineers to accelerate ML pipeline development.

The Staff Motion Planning Engineer will research and develop algorithms for motion planning in autonomous vehicles, building scalable software and interfacing with various components of the system.

Develop and optimize machine learning models for autonomous vehicles, focusing on ML model deployment and performance across various compute platforms.

Lead development of large-scale data analysis and validation workflows for autonomous driving ML. Design metrics, build datasets, run statistical error and regression analyses, collaborate with ML and software teams, and maintain AWS/Kubernetes orchestration for large-scale evaluation.

Lead development of motion planning and prediction ML models for Level 4 autonomous vehicles. Design and productionize behavior models using deep learning, generative AI, and reinforcement learning. Deploy solutions to vehicle fleets, collaborate with perception, simulation, data platform and integration teams, and report progress to leadership.

Lead and build an ML Acceleration team to define strategy and implement scalable solutions to speed ML training. Hands-on role combining technical design (distributed training, hardware and model optimization) with people management, cross-functional collaboration, impact measurement, and continuous performance improvements for production autonomous vehicle ML systems.