[ACES Team] Senior Software Engineer - Computer Vision and Machine Learning

Computer Vision and Machine Learning is the key for autonomous driving vehicles to be equipped with the capability of understanding objects in the surrounding world. You will be working with the autonomous rapid transit team to build robust, scalable object recognition subsystems over images and point clouds—from data pipelines all the way to production deployment.

Responsibilities

• Design and maintain end-to-end MLOps pipelines — including data versioning, model training, experiment tracking, deployment, and monitoring in production environments
• Research and implement transformer-based vision models (e.g., ViT, DETR, BEVFormer) to improve object recognition accuracy and stability
• Collaborate cross-functionally with hardware, software, and safety teams; coordinate project timelines and communicate technical progress to stakeholders
• Drive continuous improvement through model performance analysis and iterative experimentation

Qualifications

• Fluent C++ programming skills; proficient in Python
• BS or MS degree in Computer Science, Electrical Engineering, or related field
• Familiar with camera imaging fundamentals and digital image processing theories
• Experience with transformer-based architectures (Vision Transformer, DETR, or similar) and classic CNNs
• Hands-on experience with MLOps practices — experiment tracking, model registry, CI/CD for ML, and production monitoring
• Experience with training and performance tuning using PyTorch or TensorFlow
• Experience with ROS/ROS2 infrastructure
• Ability to manage project scope and deliverables, communicate status, and flag risks proactively
• Good communication skills and ability to self-direct

Bonus Qualifications

• Familiar with BEV (Bird's Eye View) perception models and multi-sensor fusion
• Familiar with 3D pose estimation over point clouds or images
• Experience with CUDA C/C++ and model optimization (TensorRT, ONNX)
• Experience with data pipeline orchestration tools
• Experience in tech lead or project coordination roles

We encourage candidates to apply even if they don't meet all of the above qualifications. We value skill and experience diversity — and most importantly, enthusiasm for building robust autonomous driving systems together.