PlusAI

Software Verification & Validation Engineer responsible for building quantitative safety metrics, simulation test suites, and automated regression systems for autonomous vehicle software. The role combines AV domain expertise, Python development, large-scale failure analysis, and CI/CD integration.

Join PlusAI’s Motion Planning team to develop safe, human-like decision-making and trajectory-generation systems for autonomous trucks. You’ll bring robotics and machine learning techniques from research into a production-grade, safety-critical vehicle platform.

Build and optimize the machine learning runtime powering production motion planning for autonomous trucks. This role combines high-performance C++, embedded inference, safety-critical validation, and deep debugging across the autonomy stack.

Join PlusAI as a Senior/Staff Machine Learning Engineer focused on reinforcement learning and learned motion planning for autonomous trucks. You will build end-to-end RL pipelines and deploy learned behavior-planning models across driving scenarios.

Build and deploy advanced machine learning systems for motion planning in autonomous trucks. This role owns the full ML lifecycle, from data and model development through safety validation, production deployment, and continuous improvement.

Build and scale AI-powered simulation infrastructure that validates autonomous vehicle systems and closes the gap between simulated and real-world behavior. This senior role combines scalable pipeline architecture, simulation fidelity improvements, and LLM-powered analysis workflows.

Lead the design and implementation of high-fidelity mapping and localization algorithms for autonomous trucks, combining multi-sensor data with HD maps. This principal-level role tackles challenging environments such as GPS-denied tunnels and dynamic construction zones to support safe L4 autonomy.

Senior Machine Learning Engineer focused on building BEV-based perception models for autonomous trucks using camera, LiDAR, and radar data. The role combines deep learning, multimodal sensor fusion, and production deployment for real-world vehicle autonomy.