Top Tech Jobs & Startup Jobs

Lead architecture and implementation of motion planning, trajectory generation, and optimization for autonomous trucks. Provide multi-team technical leadership, design production-quality C++ planning software, integrate with controls and perception, validate via SiL/HiL/ViL, and support on-vehicle debugging, deployment, and performance optimization to deliver safe, reliable autonomy at scale.

Develop and execute lab and field test plans to validate sensor modalities (LiDAR, radar, camera, microphones, INS). Interface with suppliers and systems/software teams to decompose requirements, perform root cause analysis, ensure automotive-grade performance, and maintain technical documentation.

Develop and own high-fidelity vehicle dynamics models and simulation platforms for autonomous truck validation. Collaborate with autonomy teams to capture requirements, run automated regression and validation pipelines, perform root-cause analysis including HIL, and support large-scale RL training and system-level V&V.

The software engineer will develop and maintain Linux software for autonomous vehicles, optimize performance, debug systems, and ensure system stability and security, collaborating with cross-functional teams.

Design and deploy object detection and tracking modules; develop ML algorithms; guide team members; improve data governance and quality assessment.

Designs and executes vehicle- and software-level test plans for autonomous trucks, collects and analyzes test data, performs root-cause analysis, implements data acquisition and automation systems, supports CI/CD and software development in Linux (C++ and scripting), and conducts on-road testing and reporting to improve system safety and performance.

Lead vehicle-level testing and software engineering for autonomous trucks: generate and execute test plans, analyze data, perform root cause analysis, develop test instrumentation and CI/CD tooling, execute on-road observer/annotator duties, and collaborate with product and engineering teams to improve safety and system performance.

Embed with one or two Autonomy teams to enable large-scale replay/recompute workflows: implement data flows, onboard models, ensure metric evaluation and visualization adoption, debug full-stack issues, document workflows, and translate team feedback into simulation platform improvements.

Lead and grow the Offline Perception team building auto-labeling pipelines and offline perception training/evaluation. Own roadmap, architecture guidance, data pipeline and infrastructure strategy, stakeholder alignment, quality/process improvements, and hiring/mentoring to deliver production-grade multi-modal perception training data to downstream teams.

Build and maintain AWS-based data pipelines and Python services that process vehicle telemetry and validation data. Compute safety and performance metrics, support release validation and automated testing pipelines, investigate pipeline failures and data anomalies, collaborate with cross-functional teams, and contribute to statistical analysis and reporting to ensure autonomous truck safety and reliability.