Tusimple was founded in 2015 with the goal of bringing the top minds in the world together to achieve the dream of a driverless truck solution. With a foundation in computer vision, algorithms, mapping, and AI, Tusimple is working to create the first commercially viable autonomous truck driving platform with L4 (SAE) levels of safety.

 

Job Description

Our deep learning team helps autonomous car sense and perceive the world.  You will play an important role in creating novel algorithms for advanced perception and apply your algorithm on terabytes of data. The successful job applicant will work with our experts in building the next-generation of autonomous sensing algorithms.

Responsibilities

  • Research and prototype developing using deep learning with a special focus on the perception problems of autonomous driving

Qualifications

  • PhD or MS in related academic program or equivalent practical experience
  • Sound understanding of deep learning literature
  • Excellent programming experience in AT LEAST ONE of the following languages:
  • C, C++, Python
  • Familiarity with at least one of the following neural network frameworks:
  • MXNet (preferred), TensorFlow, Torch, Caffe

Bonus Points

  • Related experience in autonomous driving
  • Published at top tier journals/conferences in CV/ML

Perks

  • Work with world class AI Engineers
  • Shape the landscape of autonomous driving
  • Daily breakfast, lunch, and dinner
  • Full Kitchen with unlimited snacks and fruits
  • Weekly team happy hour
  • Medical, Vision, and Dental insurance plan
  • Company 401(K) program
  • Company paid life insurance

 

TuSimple is an Equal Opportunity Employer. This company does not discriminate in employment and personnel practices on the basis of race, sex, age, handicap, religion, national origin or any other basis prohibited by applicable law. Hiring, transferring and promotion practices are performed without regard to the above listed items.

Apply for this Job
* Required
(Optional)
Almost there! Review your information then click 'Submit Application' to apply.

File   X
File   X
+ Add Another