Tasks:
- * Analyze experiment results
- * Build pretraining datasets
- * Build temporal planning models
- * Design loss functions
- * Develop trajectory prediction tasks
- * Document experiments and technical findings
- * Model multi-agent interactions
- * Optimize data pipelines
- * Process driving and simulation data
- * Reproduce research algorithms
- * Resolve CPU and I/O bottlenecks
- * Run pretraining and fine-tuning experiments
Perks/Benefits:
Skills/Tech stack required:
[Agent modeling] [Autonomous Driving] [CUDA] [Data Preprocessing] [DDP] [Deep learning] [DeepSpeed] [Distributed Training] [Fine Tuning] [GPU Training] [Hugging Face] [Hugging Face Transformers] [Linux] [LSTM] [Machine Learning] [Mamba] [Model pretraining] [Multi-Agent] [Multi-agent modeling] [NumPy] [Path Planning] [Python] [PyTorch] [Self-supervised] [Self-Supervised Learning] [Series modeling] [Shell] [Supervised Learning] [Time Series] [Time Series Modeling] [Trajectory Prediction] [Transformer]
Educational requirements:
N/A
Role(s):
[Algorithm Engineer Intern] [Autonomous Driving Algorithm Engineer] [Autonomous Driving Algorithm Engineer Intern] [Engineer Intern] [Intern] [Machine Learning Engineer] [Machine Learning Engineer Intern]