Computer Vision Research Engineer
Posted 8 months ago
Aptiv Autonomous Mobility Our real-world mobility solutions are driving us toward a safer, greener and better connected future. Aptiv is providing the “brain” and “nervous system” for vehicles that will change the face of mobility for people worldwide. Aptiv’s Autonomous Mobility team is focused on developing, and commercializing autonomous vehicles and systems that enable point-to-point mobility via large fleets of autonomous vehicles in challenging urban driving environments. With talented teams working across the globe, from Boston to Singapore, Aptiv was the first company to deploy a commercial, point-to-point autonomous ride-hailing service based in Las Vegas, Nevada. In November 2017, Aptiv acquired autonomous vehicle software startup nuTonomy, an integral part of Aptiv’s Autonomous Mobility team. With continued research, development, and both current and future commercial deployments, we are looking for talented and passionate people to join our team. Work with leading engineers, research scientists, marketers and business development experts, all while enabling the future of mobility. At Aptiv, we believe that our mobility solutions have the power to change the world. For more information, please visit www.aptiv.com/our-journey and see our www.aptiv.com/careers for opportunities. About this position We are seeking a highly motivated Computer Vision Research Engineer. The ideal candidate knows Convolutional Neural Networks inside out, is familiar with the relevant Computer Vision literature and has extensive experience implementing machine learning algorithms in frameworks like PyTorch or Tensorflow. The candidate will have ownership for their own projects, but will work closely with senior researchers on the team. This position will be with the Machine Learning team which previously released the PointPillars object detection method and the large-scale nuScenes dataset for autonomous driving. We encourage publishing in academic conferences and journals.
The following are examples of projects that we are excited about:
- Active learning: Use Deep Learning to automatically infer which images or scenes should be annotated by a human annotator.
- Data mining: Automatically mine large volumes of data for rare classes, corner cases and to cover all types of scenarios.
- Taxonomies & data collection: Be the driving force behind standardizing Autonomous Vehicle class taxonomies, requirements and supervise our data annotation pipelines.
- Metrics: Design novel metrics for object detection, tracking, etc. and study how metrics correlate across different parts of an Autonomous Vehicle.
- nuScenes v2.0: Plan, implement and supervise new public datasets, including their devkits, baselines, evaluation code and academic papers.
- Masters degree
- Expert knowledge in PyTorch and Python
- Strong background in Machine Learning and Computer Vision literature
- Strong background in data structures and algorithms
- Hands-on Computer Vision projects
- Good software engineering skills
- At least one publication in top Computer Vision conferences (CVPR, ICCV, ECCV etc.)
- Familiarity with leading Computer Vision datasets
- Desire to work in a fast-paced startup environment
Job tags: Autonomous Driving Computer Vision Data Mining Deep Learning Engineering Machine Learning Python PyTorch Research TensorFlow