Senior Perception Engineer, Obstacle Foundation Models

What you'll do

• Develop the technical design, architecture, and roadmap for 3D obstacle perception in autonomous driving.
• Design and implement 3D perception models using multi-camera inputs and multi-sensor fusion.
• Build production-grade deep learning models using large-scale pretraining, distillation, and parameter-efficient fine-tuning.
• Maintain KPI frameworks to quantify performance and analyze large-scale datasets to identify and fix failure modes.
• Define data and labeling requirements and prioritize data collection for perception model training.
• Implement model-assisted workflows including active learning, auto-labeling, and vision-language models.
• Optimize perception solutions for safety, latency, and resource usage to ensure production readiness.

What we're looking for

• PhD with 4+ years, MS with 6+ years, or BS with 8+ years of experience in Computer Science, Computer Engineering, or a related field.
• Hands-on experience developing deep learning-based perception systems for complex real-world problems.
• Proficiency in PyTorch and a track record of taking models from prototype to production.
• Experience in data-driven development, including collaboration on data strategy, labeling quality, and iterative model improvement.
• Strong programming skills in Python and/or C++ to build high-performance, production-quality software.
• Experience designing and deploying perception solutions for autonomous driving or robotics using camera-based deep learning at scale (preferred).
• Experience architecting DNN-based perception pipelines on embedded or real-time platforms with optimization for latency and memory (preferred).
• Strong publication record or recognized contributions in deep learning, computer vision, or autonomous systems at leading conferences (preferred).