Develops motion planning algorithms, collaborates with engineering teams, and optimizes performance for autonomous vehicle decision-making.

As a Software Engineer in the Labeling Backend team, you will design and implement systems for managing large datasets for autonomous systems, collaborating with ML teams to enhance model improvements.

The Research Engineer will improve dataset quality for self-driving systems by designing algorithms for auto-labeling and data monitoring, collaborating with teams, and enhancing model performance.

As a Senior C++ Engineer, you'll design and implement simulation infrastructure, ensure accuracy and efficiency of runs, and collaborate with teams for integration and performance analysis.

As a Senior Financial Controller, you'll oversee financial compliance and reporting across multiple entities, ensuring adherence to US GAAP and regulatory standards, while leading audits and maintaining internal controls.

The QA Engineer will design and execute testing plans for autonomous driving software, analyze test scenarios, and document outcomes. Collaboration with cross-functional teams is crucial for improving test processes and safety metrics.

The Corporate Counsel will provide legal guidance on contracts and compliance issues related to autonomous technology, advising multiple teams on regulatory matters.

Lead the analytics function for autonomous driving, focusing on evaluation, experimentation, mentoring analysts, and building automated analysis pipelines.

Develop motion planning algorithms for autonomous robots, ensuring safety, smoothness, and reliability in navigation. Collaborate with various teams for improvement and evaluation.

Design and optimize control systems using modern C++, focusing on trajectory tracking and real-time performance constraints, while collaborating with cross-functional teams.

Design and develop advanced data annotation tools, integrating with external platforms and improving user experience for 2D and 3D labeling workflows.

The Machine Learning Engineer will develop and optimize models, manage datasets, enhance training pipelines, and collaborate across teams to innovate in autonomous vehicle technology.

Develop and maintain the software framework for autonomous vehicle autopilot systems, focusing on performance, safety, and reliability, while implementing automated testing processes.

Lead the development of a scalable data processing infrastructure for ML and simulation teams, focusing on integration, prototyping, and mentorship.

Design and maintain data pipelines and infrastructure for processing large datasets from autonomous vehicles, optimizing for performance and usability.

Develop and maintain low-latency, real-time interfaces for a Remote Control system aiding autonomous cars and robots, collaborating with multiple teams to enhance performance and user experience.

Design, develop, and operate metrics infrastructure for autonomous vehicles, working on data models, storage solutions, and scalable pipelines in collaboration with development and analytics teams.

Join Avride as a Data Analytics Engineer to build ETL pipelines, manage datasets, write SQL queries, and create dashboards for data insights.

As a Machine Learning Engineer, you will design, train, and deploy ML models for motion planning, develop data pipelines, and integrate models for real-time use in autonomous vehicles.

Design and develop system-level software for Linux in autonomous vehicles. Integrate hardware and software, ensuring reliability and efficiency with management tools.