Computer Vision / Machine Learning Researcher for Sensor Fusion with Deep Learning

Job description

Maps rule the world. They inform and underpin some of the most crucial decisions that are made in society—but the world is moving so fast that maps everywhere get outdated quicker than any single player can update them. That’s where Mapillary comes in. We allow anyone, anywhere to update maps at scale, using nothing but cameras. We apply computer vision to street-level imagery to generate map data at scale, so that people and organizations everywhere can build better maps.


We are looking for a Computer Vision / Machine Learning Researcher, who will investigate the problem of sensor fusion (from multiple industrial-type RGB cameras, stereo-images, LiDAR, RADAR, etc.) using deep learning. The successful applicant will take ownership in developing, communicating and exchanging research insights within an academic and industrial consortium. The goal is to generate and publish ideas in top-level computer vision and machine learning conferences (CVPR, ICCV, NeurIPS, etc.).

Requirements

  • Ph.D. degree in Computer Science (specialization in Computer Vision / Machine Learning)
  • Proven scientific track record (Publications in top-level conferences and high-impact journals)
  • Experience in 3D modeling with state-of-the-art Structure from Motion & Multi-view Stereo pipelines like COLMAP and OpenSfM
  • Highly skilled in PyTorch, fluent in python; CUDA is a plus
  • Knowledge about data annotation processes and quality assurance is a plus
  • Excellent communication skills, both verbal and written, and speaking German are great assets
  • Ability to travel to project meetings and conferences

The position will be based in Austria (with the possibility of working in our office in Graz or remotely), and the opportunity to work with existing team members all over the world.