Description

Role Description:

Develop and implement deep learning models for autonomous vehicle motion planning, utilizing expert demonstrations. You will design, evaluate, and optimize machine learning models for safe and efficient real-world navigation.

 Responsibilities:

• Implement, train, evaluate, and deploy deep learning models for autonomous vehicle motion planning.
• Optimize and test real-time motion planning algorithms.
• Design, conduct, and analyze experiments for both novel approaches and performance improvements.
• Process large datasets, both structured and unstructured.
• Staying up to date with relevant research and projects.

Requirements

• Bachelor's degree or higher in Computer Science or other engineering field.
• Strong foundation in machine learning principles and deep learning techniques.
• Familiarity with motion planning algorithms.
• Proficiency in Python and experience with deep learning frameworks such as PyTorch.
• Comfortable working in Linux environment.
• Strong problem-solving and analytical skills.
• Ability to quickly learn and adapt to new technologies and research findings.
• Comfortable working with large datasets.
• Excellent communication and teamwork skills. 

Preferred Skills and Qualifications:

• Experience with imitation learning or reinforcement learning.
• Experience developing in C++ / CUDA for real-time systems.
• Familiar with the autonomous-vehicle domain.