Vehicle Planning Research Engineer

About the Role:

TuSimple is the self-driving technology company with a mission to bring automation to the trucking industry. TuSimple's Planning Research Team plays a critical role in generating optimized trajectories for our self-driving trucks. This Vehicle Planning Research Engineer would support TuSimple's planning module, which includes important components such as lane change decision, motion planning, and trajectory selection. 

Planning Team Responsibilities:

• Deliver high-quality and reliable code for planning modules on autonomous driving trucks 
• Develop the cutting edge stochastic optimization algorithms in decision making 
• Gain experience in convex optimization algorithms for motion planning 
• Build advanced models for machine learning based planning algorithms 
• Collaborate with other engineers to conduct system integration and tests.

Example Vehicle Planning Research Projects include:

• Improve lane change algorithms to make our lane change natural, smooth and safe
• Longitudinal and Lateral joint optimization to handle sudden cut-in and complicated merge scenarios
• Perception and prediction uncertainty handling in motion planning
• Learning based planning algorithms (both deep learning and reinforcement learning)

What You Will Need: 

• Location: Ability to work from TuSimple’s San Diego Office three days a week is required for this role. 
• Education: At least a Bachelor’s Degree is needed for this role. 
• Experience: 
  • At least 4 years of directly related experience is required for this role. 
  • Product-quality code in C++ and/or Python.
  • Knowledge and experience in advanced learning algorithms include deep learning, reinforcement learning, inverse reinforcement learning, GAN
  • Knowledge and experience in convex optimization, non-linear optimization, stochastic optimization, Markov decision process, graphic search algorithm
  • Experience in designing and building data pipelines.

What Will Set You Apart:

• Masters or a PhD in Computer Science, Robotics, Mechanical Engineering, Math/statistics or other related fields.
• Autonomous Vehicle Industry Experience is highly preferred, but not required. 
• Advanced Driver Assisted Systems (ADAS) experience is also preferred. 
• Demonstrated ability to prototype and implement controllers on physical systems is preferred, too.

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