Supports engineering quality assurance across systems and software development, reviewing work products, strengthening traceability, assessing process adherence, and preparing evidence for product milestones and releases.
Architect and evolve foundational frameworks for an autonomous driving stack, setting technical direction for real-time C++ systems and improving reliability, testing, and integration across autonomy teams.
Design, implement, and support secure enterprise application integrations and automation, maintaining reliable data flows across business systems while improving data integrity, process efficiency, and user experience.
Lead safety-critical program execution for autonomous vehicles, coordinating safety engineering, verification and validation, risk management, and operational readiness from concept through deployment.
Leads safety-critical program execution for autonomous vehicles, connecting safety goals, engineering requirements, verification and validation evidence, risk management, and operational readiness through deployment.
Annotate and quality-check 2D images and 3D sensor data, including LiDAR, creating accurate labels that help train AI systems to recognize surroundings in autonomous trucks.
Vous annoterez et vérifierez des images 2D et des données de capteurs 3D, notamment LiDAR, afin de produire des données fiables qui entraînent les systèmes d’IA des camions autonomes.
Lead the Metrics & Analysis team, combining people management with hands-on data analysis to develop performance and software quality metrics, tools, and insights for engineering decisions.
Lead simulation engineers and define the strategy, tools, and scenario coverage for verifying autonomous truck perception and behavior, producing safety evidence and release-readiness insights.
Lead a team responsible for hardware-in-the-loop verification and validation of an autonomous truck, owning test strategy, safety evidence, and technical direction while coordinating campaigns and cross-functional partners.
Own vehicle-level verification and validation for L4 autonomous trucks, leading test strategy, engineering teams, scenario-based coverage, and vehicle-data analysis to support safety cases and program decisions.
Lead a machine learning team to develop active sensor-based perception capabilities for autonomous trucks, overseeing the entire perception lifecycle from data requirements to deployment.
Design and deploy production machine-learning models and software for real-time multi-object tracking, sensor fusion, and state estimation, improving the safety and robustness of autonomous truck operations.
As a Quality Control Engineer on the map enablement team, you will ensure the accuracy and completeness of high-definition map datasets for autonomous trucks through rigorous quality control processes.
As a Senior Machine Learning Engineer – Camera Models, you will develop and deploy machine learning models that enhance camera-based perception for autonomous trucks.
Develop and deploy machine learning models for camera-based perception, enhancing the autonomy stack for safe and reliable autonomous driving in freight environments.
Own system-level simulation testing for autonomous driving software, developing V&V strategies and scenario coverage while analyzing results to improve the robustness and safety of self-driving technology.
As a Staff Software Engineer focused on Simulation Vehicle Modeling, you will own the architecture for scalable vehicle modeling and simulation, ensuring high-fidelity models and robust testing frameworks for autonomous driving software.
As a Staff Machine Learning Engineer specializing in BEV and Multi-Modal Perception, you will lead the development of advanced models that integrate data from various sensors to enhance autonomous driving capabilities.
As a Senior Machine Learning Engineer focused on localization, you will design and deploy ML models for ego-motion estimation, ensuring robust performance in autonomous vehicles.
As a Machine Learning Engineer II – 3D Perception, you'll advance perception capabilities by developing and improving machine learning solutions for autonomous trucks.
The Auto Tagger team is the engine behind our data flywheel, responsible for translating petabytes of raw, multi-modal vehicle data into a highly curated library of critical driving scenarios.
Embed with autonomy teams to scale Torc Sim adoption, integrate perception models into replay and evaluation workflows, and improve data pipelines, metrics, and visualization across the simulation stack.
As an Autonomy Data Engineer Level 2, you will design and maintain data infrastructure, ensuring reliable data ingestion and curation for autonomous vehicle systems.
Page 1 · 31 results
