Intern - RL Controls Research Engineer

Plus is a global provider of highly automated driving and fully autonomous driving solutions with headquarters in Silicon Valley, California. Named by Forbes as one of America’s Best Startup Employers and Fast Company as one of the World’s Most Innovative Companies, Plus’s open autonomy technology platform is already powering vehicles in commercial use today. Working with one of the largest companies in the U.S., vehicle manufacturers, and others globally, Plus is helping to make driving safer, more comfortable, and more sustainable. Plus has received a number of industry awards and distinctions for its transformative technology and business momentum from Fast Company, Forbes, Insider, Consumer Electronics Show, AUVSI, and others. If you’re ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams.

Responsibilities

• Create environment to simulate Adversarial and extreme vehicle behavior.
• Establish robustness envelope of existing controllers and enhance it with newer approaches
• Create framework for Learning Control Policies using Reinforcement and Generative Adversarial Imitation Learning
• Responsible for the conceptual design of software for reinforcement-learning-based controllers

Required Skills

• MS or PhD in Reinforcement Learning, Robotics, or related field E
• xperience with Imitation Learning, Reinforcement Learning, modern Neural Network architectures
• Expertise with Python, willingness to do some C++ development as needed.
• Experience model development & training and with modern frameworks (e.g. PyTorch)
• Strong track record of publishing papers and/or deploying real-world applications

Your opportunities joining PlusWork, learn and grow in a highly future-oriented, innovative and dynamic field.Wide range of opportunities for personal and professional development.Catered free lunch, unlimited snacks and beverages.Highly competitive salary and benefits package, including 401(k) plan.