Machine Learning Fellowship (6-12 months)

Role Summary

The perception and machine learning team at IECC is tasked with applying machine learning to the automotive industry. This includes applications like autonomous driving, manufacturing, material design, etc. You will develop state-of-the-art AI solutions to tackle complex challenges using the latest machine learning techniques on large datasets.

Responsibilities

• Driving data pre-processing including checking labels, formatting, etc.
• Supporting the project team in building data pipelines for training deep neural networks.
• Benchmarking and reporting performance of various neural network models.
• Researching new network architectures for time series prediction and anomaly detection.
• Researching new network architectures to enhance the perception of the environment with a focus on optical sensors.
• Exploring supervised and unsupervised learning methods for estimating road participants' depth, motion, and velocity.
• Researching various neural networks for interpreting camera images (object detection, panoptic segmentation) and trajectory/motion planning.
• Fusing different neural networks to utilize shared resources to reduce memory and computation footprints.

Qualifications

• Must be enrolled at a University/College or graduation date must be within the last six months in a Masters or PhD program.
• Must have a cumulative GPA of at least 3.0.
• 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.
• Independent work, initiative, motivation, ability to work in a team.