Tasks:
- * Build lane-change evaluation systems
- * Deploy and validate models on vehicles
- * Develop lane-change scenario checkers
- * Improve lane-change safety and success rate
- * Manage model releases and testing
- * Mine and curate training data
- * Monitor simulation and real-world performance
- * Research lane-change planning algorithms
- * Train and optimize lane-change models
Perks/Benefits:
- + Collaboration with autonomous driving engineers
- + End-to-end model development experience
Skills/Tech stack required:
[A/B] [A/B Testing] [Autonomous Driving] [Autonomous Driving Planning] [B testing] [C++] [Change planning] [Data Mining] [Decision Making] [Decision-making algorithms] [Deep learning] [Driving Planning] [End to End] [End-to-end neural networks] [Lane change] [Lane-change planning] [Linux] [Lua] [Model Training] [Model Tuning] [Neural Networks] [On-vehicle deployment] [Python] [PyTorch] [Simulation testing] [Vehicle Deployment]
Educational requirements:
[Bachelor's Degree]
Role(s):
[Algorithm Engineer] [Algorithm Intern] [Autonomous Driving Algorithm Intern] [Engineer] [Intern] [Learning Engineer] [Machine Learning Engineer] [Planning Algorithm Engineer]