Avride
Machine Learning Engineer
About this role
Avride seeks a Machine Learning Engineer to develop and deploy deep learning models for autonomous vehicles and delivery robots. You'll build scalable ML solutions using advanced architectures like CNNs and Transformers, manage large datasets, and optimize models for real-world autonomous systems.
What you'll do
- Design, implement, and refine deep learning models for autonomous navigation and perception tasks
- Curate, preprocess, and augment large-scale datasets for training and evaluation
- Develop efficient training pipelines with distributed training and hyperparameter tuning
- Optimize model inference performance and deployment across hardware platforms
- Research and experiment with emerging deep learning techniques to improve performance
- Collaborate with researchers, engineers, and robotics experts on integration
What they're looking for
- Python and ML frameworks (PyTorch, TensorFlow, or JAX)
- Computer vision, large language models, or generative AI expertise
- Neural network development and deployment experience
- C++ and SQL
- PySpark, NumPy, and SciPy
- Cloud platforms and ML orchestration tools
- Data collection and preprocessing
- Research paper analysis and technical documentation review
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Avride
Avride develops autonomous vehicle and delivery robot technology, building the computational infrastructure, data systems, and localization platforms that enable autonomous driving development. The company is hiring backend engineers, ML infrastructure specialists, data platform engineers, robotics software engineers, and site infrastructure engineers to scale its simulation, training, logging, and operational systems.
View all jobs at AvrideLikely interview questions
- Walk us through a deep learning project where you developed and deployed a neural network model end-to-end. What frameworks did you use, and what challenges did you face?
- Describe your experience managing and preprocessing large-scale datasets. How have you handled data augmentation and quality assurance in production systems?