Develop and implement state-of-the-art trajectory optimization algorithms to ensure safe and comfortable autonomous vehicle motion. Collaborate cross-functionally with teams in decision planning, prediction, and vehicle control to build integrated, scalable software solutions.
Lead a diverse team of engineers to develop and maintain large-scale AI model and software evaluation frameworks for autonomous vehicles. Drive innovation in data warehousing and analysis while ensuring rigorous validation of ML model performance and safety.
The Perception Engineer will design, develop, and implement features in the codebase while architecting solutions for autonomous vehicle technology. They are responsible for training and deploying AI models, analyzing performance, and iterating on solutions to enhance system capabilities.
Lead the architecture and scaling of a modern frontend ecosystem to create critical web visualization tooling for machine learning engineers. Drive cross-team standards and collaborate with UX and data teams to improve autonomous vehicle system feedback loops.
Technically oversee the design and deployment of an Embodied AI and LLM-based monitoring framework for off-board scenario understanding and root cause analysis. Lead the creation of an evaluation layer to assess autonomous vehicle driving intelligence and safety using fleet data and drive logs.
Lead and grow a high-performing team of full stack engineers to build AI data applications for ML dataset generation and search. Define the technical vision for metadata storage and AI adoption strategies to accelerate development cycles.
Build and enhance Agentic AI tooling and high-scale ML infrastructure using Kubernetes to empower developer productivity. Partner with researchers to optimize distributed training jobs and resolve system-level bottlenecks to maximize GPU utilization.
Develop and implement performance-critical motion control and trajectory optimization algorithms for autonomous robotaxis. Collaborate with cross-functional teams to build integrated solutions and mentor junior engineers on product-focused development.
Lead the AV Behavior Understanding and Evaluation team to define standards for safe and assertive autonomous driving. Drive the design, evaluation, and scaling of system behaviors using data-driven insights from simulation and real-world testing.
Develop large-scale solutions for mining challenging driving scenarios to improve autonomous driving model performance. Collaborate with infrastructure teams to create continuous learning workflows and provide statistical insights on model robustness.
Design and implement software pipelines for autonomous vehicle localization systems and collaborate with mapping, perception, and motion planning teams. Provide technical leadership through code reviews and guidance for junior team members to ensure software quality and efficiency.
Develop and integrate planning algorithms for autonomous driving while building a robust and scalable codebase. Interface with system components via CI/CD pipelines and provide mentorship to junior team members.
Develop and train ML pipelines for multimodal sensor data to identify critical driving scenarios and edge cases. Build scalable data preprocessing pipelines and monitor production model health and performance.
Design and assess AV behavior competencies using data-driven assessment from on-road and simulation modalities. Develop metrics, automate result analysis, and provide strategic insights to improve AV performance and safety.
Define and execute motion planning and prediction projects to improve autonomous vehicle navigation in complex traffic. Design and deploy ML behavior models using generative AI and reinforcement learning onto vehicle fleets.
