Senior Edge AI Perception Engineer

About the role

AION Robotics builds best in class autonomous vehicles designed for critical infrastructure monitoring, construction, mining and energy. Our vehicles operate in the toughest off-highway environments, where safety, accuracy, and efficiency are paramount. We are seeking a highly experienced Edge AI Perception Engineer to design, optimize, and deploy cutting-edge deep learning models for real-time autonomous vehicle perception systems.

Responsibilities

• Build and manage optimized neural network pipelines tailored for edge deployment in autonomous vehicle systems.
• Implement, compress, and optimize models (pruning, quantization, scheduling) to run on GPU, DLA, and Tensor cores.
• Work with architectures including monocular depth models, YoloX, PeopleNet, ResNet, and others.
• Leverage NVIDIA DeepStream, TensorRT, CUDA, and TAO Toolkit to create high-performance perception pipelines.
• Manage model/hardware resource allocation across GPU/DLA for real-time scheduling and execution.
• Optimize pipelines “lens-to-detections” meeting ultra-low latency constraints on embedded devices such as NVIDIA Orin & Thor.
• Apply real-time geometric transforms to object detections and semantic segmentation results for geo-referencing and LiDAR point cloud filtering.
• CUDA accelerated 3D Terrain mapping
• Develop and maintain automated data collection pipelines, including dataset formatting, labeling workflows (CVAT), and fine-tuning for custom training.
• Implement real-time dewarped camera pipelines using GMSL drivers, VIC, and ARGUS APIs on embedded platforms.
• Collaborate with hardware engineers to achieve consistent calibration and synchronization across multiple sensors.
• Stay up to date with bleeding-edge advancements in neural networks, edge AI optimization, and autonomous perception.
• Rapidly prototype and validate new models and methods for production deployment.

Qualifications

• Direct real-world experience in computer vision, deep learning, or edge AI systems.
• Strong proficiency with CUDA, TensorRT, NVIDIA DeepStream, TAO Toolkit, PyTorch/TensorFlow.
• Demonstrated experience with model optimization techniques (e.g., pruning, quantization, distillation, scheduling).
• Hands-on experience deploying AI pipelines to embedded edge platforms (preferably NVIDIA Jetson Orin or Thor).
• Expertise in object detection, semantic segmentation, and depth estimation.
• Solid understanding of real-time embedded system constraints and low-latency optimization strategies.
• Strong programming skills in C++ and Python.

Benefits

• Competitive compensation, equity opportunities, and comprehensive benefits.
• Annual bonus & base salary reviews.
• Personalized PTO.
• Wellness program.
• 401K retirement plan.
• Medical, Vision & Dental coverage.
• Short and long-term disability insurance.
• Life insurance.