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Date Added: Wed 09/06/2021

Localization & Calibration - Research Engineer/Scientist

Boston, MA, US
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Company: TUSIMPLE, INC.

Job Type: Permanent, FullTime

Job Description
 

This opportunity is located in San Diego, CA.  Remote friendly during COVID-19 

You can apply to the job with this email address: #removed#

TuSimple Company OverviewCome join a higher calling and find a deeper purpose!   

TuSimple is a fully commercialized autonomous trucking company.   As a multi-national Artificial Intelligence Technology Company, we are at the epicenter of the Autonomous Vehicle Universe. Our breakthroughs are leading the industry in autonomous trucking.  

While inventing the framework of Autonomous Driving, our live fleet of autonomous Trucks have fully evolved land freight.    TuSimple is leading the way by hiring the most talented researchers, engineers, and scientists.  

TuSimple was founded half a decade ago 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 Artificial Intelligence, TuSimple has created the first commercially viable Autonomous Freight Network.

Job Description

Out team, Calibration and Localization, is a significant player in the autonomous driving system. At Tusimple, our team is mainly responsible for sensor calibration and ego localization.  You will work with the best talents to develop the state-of-art algorithms for online/offline sensor calibration and ego localization that meet ASIL level functional safety.

Example projects we are working on include:

  • Provide relative poses of various sensors in millimeter and <0.1 degree resolution
  • Real-time correction of sensor pose due to roughness of the truck while driving
  • Develop centimeter-accuracy ego localization even when GPS is out of service
  • Benchmark of algorithms to ensure their performance for agile development
Responsibilities

  • Deliver high-quality and product-level code for modules on autonomous driving trucks
  • Formulate ill-defined problems with data driven approach for autonomous trucks driving
  • Be responsible for design, implementation, and evaluation of the cutting edge and sophisticated algorithms
  • Work on different sensors such as camera, LiDAR, radar, GNSS/IMU and etc
  • Experience non-linear optimization algorithms and non-convex problem
  • Collaborate with other engineers to conduct system integration and tests.
Qualifications

  • MS in Computer Science, Computer Vision, Machine Learning, Robotics, Math/Statistics or other related fields
  • Product-quality coding skill in Python or C/C++
  • Solid knowledge and insight understanding of at least one of the following domains:
    • computer vision: feature extraction/matching, SLAM, SfM, VO/VIO, multi-view geometry
    • point cloud: feature extraction, registration, (un)distortion
    • state estimation: Bayesian modeling, signal process, KF/EFK, factor-graph, non-linear optimization, statistical sampling
Preferred:

  • PhD in Computer Science, Computer Vision, Machine Learning, Robotics, Math/Statistics or other related fields
  • Publications in top journals or conferences in the related fields
Perks

  • 100% employer-paid healthcare premiums for you and your family
  • Work visa sponsorship available
  • Relocation assistance available
  • Breakfast, lunch, and dinner served every day
  • Full kitchens on every floor with unlimited snacks, drinks, special treats, fruits, meals, and more
  • Stock options / equity
  • Gym membership reimbursement
  • Monthly team building budget
  • Learning/education budget  
  • Employer-paid life insurance
  • Employer-paid long and short disability
  

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.

 


This opportunity is located in San Diego, CA.  Remote friendly during COVID-19 

You can apply to the job with this email address:  

#removed#  
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