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2026 Campus Autonomous Driving Algorithm Engineer

UISEE Technologies

Beijing, Beijing, ChinaOn Site

Original Job Summary

Job Overview

UISEE Technologies is looking for a 2026 Campus Autonomous Driving Algorithm Engineer to work on end-to-end autonomous driving algorithms, platform construction, and engineering validation.

Responsibilities

  • Conduct pre-research, engineering, and validation of end-to-end autonomous driving algorithms.
  • Develop and maintain a data closed-loop platform for autonomous driving.

Qualifications

  • Solid foundation in deep learning and proficiency with frameworks like TensorFlow and Pytorch.
  • Familiarity with autonomous driving perception techniques such as object detection, tracking, BEV, and Occupancy, with additional background in prediction and planning.
  • Experience with end-to-end autonomous driving algorithms and frameworks is preferred.
  • Experience in deploying models on edge devices and performance optimization is a plus.
  • Strong engineering capabilities with proficiency in Python and C++.
  • Passion for innovation and the drive to develop practical technological solutions.

Key skills/competency

  • Deep Learning
  • TensorFlow
  • Pytorch
  • Autonomous Driving
  • Object Detection
  • Edge Deployment
  • Python
  • C++
  • Algorithm Engineering
  • Data Platform

How to Get Hired at UISEE Technologies

🎯 Tips for Getting Hired

  • Customize your resume: Highlight deep learning and autonomous driving expertise.
  • Showcase projects: Detail end-to-end algorithm development experience.
  • Prepare technically: Brush up on TensorFlow, Pytorch, Python, and C++.
  • Research UISEE Technologies: Learn about their innovations and projects.

📝 Interview Preparation Advice

Technical Preparation

Review deep learning frameworks and libraries.
Practice TensorFlow and Pytorch coding exercises.
Simulate autonomous driving algorithm improvement.
Optimize model deployment techniques for edge devices.

Behavioral Questions

Describe a challenging technical project.
Explain teamwork in algorithm research.
Discuss problem-solving under pressure.
Share experiences with innovative solutions.