Jobs at Motional

Develop and maintain high-performance simulation, analysis, debugging, visualization, and automated root-cause-analysis tools for autonomous driving systems. Build C++ and Python tooling, local or cloud-based rerun systems, GUI debuggers, and 2D/3D visualizers. Collaborate with planning and controls engineers, optimize tools for high-throughput data, and support autonomy stack development and testing.

Design and build scalable data infrastructure, backend services, data discovery and lineage systems, and fault-tolerant pipelines processing petabytes of data. Lead system design, code reviews, and technical contributions while developing cloud-based ETL solutions. Collaborate with machine learning and autonomy teams to improve data access, processing, and platform adoption.

Build and evolve internal developer platforms, backend services, CI/CD pipelines, build systems, toolchains, and productivity tooling. Partner with engineering teams to identify workflow bottlenecks, improve reliability and observability, monitor distributed systems, resolve issues, and contribute to architecture and technical roadmaps. The role requires software engineering experience, programming expertise in Python, Go, or C++, Unix knowledge, and experience with cloud infrastructure and infrastructure-as-code.

Design, build, and maintain a web-based semantic map annotation editor and 3D visualizations that handle terabyte-scale map data. Optimize performance, automate map generation, integrate with ML teams, write design docs, resolve issues, and improve user workflows for efficient map editing and validation.

Design, build, and deploy core ML infrastructure components on Kubernetes. Develop scalable services for data ingestion, processing, training, and evaluation. Write maintainable code for high-throughput, petabyte-scale systems. Own features end-to-end from design through production and operation to accelerate autonomous vehicle model development.

The ML Systems Engineer will optimize distributed training systems, develop high-performance GPU kernels, and ensure efficient data pipelines for machine learning models.

Motional seeks a Senior Cybersecurity Engineer for Defense Operations to enhance security, conduct incident response, and optimize cybersecurity practices across teams.

Design, implement, and optimize perception algorithms (detection, tracking, segmentation) using camera, lidar, and radar. Build sensor fusion, productionize models for embedded real-time systems, deploy to vehicle fleets, analyze large datasets, collaborate cross-functionally, and mentor junior engineers.

Design and implement production-ready motion planning algorithms and scalable software for autonomous vehicles. Lead system-level architecture, define multi-quarter technical roadmaps, mentor engineers, coordinate across prediction/behavior/tracking teams, and drive on-road reliability, testing, and CI-driven development.

Design and build internal developer platforms, backend services, CI/CD pipelines, and toolchains to improve developer productivity. Partner with engineering teams to identify bottlenecks, enhance reliability, scalability, observability, and contribute to system architecture and roadmaps.

Lead architecture and implementation of low-latency, reliable vehicle-to-cloud data pipelines and in-vehicle software. Own system requirements, mentor engineers, run code reviews, and collaborate across product, cloud, test, and operations to deploy telemetry, remote control, and passenger-facing features.

The intern will conduct research on driving behavior, collaborate across teams, utilize large datasets, and publish results related to Machine Learning.