The perception and machine learning team at Volkswagen's Innovation & Engineering Center California (IECC) is tasked to apply machine learning to the automotive industry, specifically in areas like autonomous driving, manufacturing, and material design. They aim to develop state-of-the-art AI solutions to solve complex problems by leveraging the latest machine learning techniques on large datasets, enabling safe and robust automated driving.
Requirements
- Strong Python programming skills.
- Good experience using Linux.
- Experience with deep learning frameworks such as TensorFlow and PyTorch.
- Good knowledge of image processing and machine learning.
Responsibilities
- Driving data pre-processing including checking labels, formatting, etc.
- Support project team in building data pipelines for training deep neural networks.
- Benchmarking and reporting of various neural network models performance.
- Research into suitable new network architectures to for time series prediction, and anomalies detection.
- Research into suitable new network architectures to improve the perception of the environment with a focus on optical sensors.
- Research on supervised and unsupervised learning methods to estimate road participants' depth, motion, and velocity.
- Research on various neural networks for the interpretation of camera images (object detection, panoptic segmentation) and trajectory/motion planning.
Other
- Six Month Minimum commitment
- Masters or PhD candidates only.
- We are unable to consider International Students/OPT or CPT at this time.
- Must be enrolled at a University/College or Graduation date must be within the last six months.
- Must have a cumulative GPA of at least 3.0.
- Independent work, initiative, motivation, ability to work in a team.
