Perception Research Engineer

About the Perception Team: 

Our Perception Research Engineers are TuSimple's semi-truck's "eyes and ears." They work on software that helps the semi-truck understand what's happening around it, like recognizing other vehicles, pedestrians, and road signs. This role ensures the semi-truck accurately "sees" its environment using sensors like cameras, LiDAR, and radar. The Perception Team develops cutting-edge perception technologies to help our truck perceive the world. 

Some Perception Project Examples include:

• 2D/3D perception including detection, segmentation, BEV-related 3D scene understanding, etc, in challenging real-world scenarios.
• Multi-sensor fusion, tracking, and state estimation using camera, LiDAR, RADAR, etc.

What You Will Do: 

• Create novel and cutting-edge algorithms for autonomous driving trucks, using camera, LiDAR, and RADAR
• Develop algorithms of perception to solve the most challenging perception problems and apply solutions to the fleet of trucks at scale. 
• Collaborate with other talents in this autonomous vehicle industry by creating the next generation of autonomous sensing algorithms.
• Use machine learning frameworks like TensorFlow or PyTorch, and software platforms specific to robotics and perception such as Robotic Operating System (ROS).
• Research in deep learning and machine learning for the most challenging perception problems, including 2D/3D perception, sensor fusion, tracking, state estimation, etc.
• Deliver high-quality, robust, and reliable codes for the perception system on the L4 autonomous driving trucks.

What You Will Need: 

• Location: Ability to work from TuSimple's San Diego Headquarters at least three days a week is required for this role. 
• Education: At least a Bachelor's Degree is required. 
• Experience:
  • At least 3 years of professional experience in applying deep learning, machine learning, or computer vision algorithms on a large scale and real-world data.
  • Extensive experience and strong knowledge in perception systems.
  • Experience with camera, LiDAR perception, RADAR perception, sensor fusion, tracking, state estimation, or a similar field.
  • Production-quality coding skills in Python and/or C++.
  • Experience with Linux and deep learning frameworks such as PyTorch, Apache Mxnet, and TensorFlow.

What is Preferred:

• Master’s Degree in Computer Science, Electrical Engineering, or related field.
• Ph.D. in Computer Science, Electrical Engineering, or related field.
• Prior academic or industrial experience in working with autonomous vehicles or perception systems.
• Track record of publishing in top-tier computer vision or machine learning conferences and/or journals.
• Experience in designing and deploying algorithms for real-world safety-critical systems.

TuSimple:

TuSimple is a global autonomous driving technology company headquartered in San Diego, California, with operations in the United States and Asia. Founded in 2015, TuSimple is developing a commercial-ready, fully autonomous (SAE Level 4) driving solution for long-haul heavy-duty trucks. TuSimple aims to transform the $4 trillion global truck freight industry through the company's leading AI technology, which makes it possible for trucks to drive safely autonomously, operate nearly continuously, and reduce fuel consumption by 10%+ relative to manually driven trucks. Global achievements include over 200 Patents, the world's first fully autonomous, 'driver-out' semi-truck run on open public roads in the U.S. and China, and development of the world's first Autonomous Freight Network (AFN).

TuSimple’s Benefits:

• 100% employer-paid healthcare premiums for your spouse or domestic partner, your dependents, and you 
• Unlimited snacks, drinks, special treats, fruits, meals, and more available
• Monthly Gym Membership reimbursement
• Monthly team building budget
• Free Coursera Enterprise Account
• Annual Tuition Reimbursement 
• Employer-paid life insurance, long, and short term 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.

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