MLE Internship, Pony.ai

• Currently pursuing a Masters or PhD program or a related discipline
• Strong programming skills in C/C++ or Python
• Solid understanding of CPU or GPU execution model, e.g. threads, registers, cache, memory, cost and performance trade-off, etc
• Experience in benchmarking, profiling and validating performance
• Strong communication skills and ability to work cross-functionally between software and hardware teams

Desirable

• The ML Infrastructure team at Pony.ai provides a set of tools to support and automate the lifecycle of the AI workflow, including model development, evaluation, optimization, deployment and monitoring
• As a Machine Learning Engineer Intern in ML Runtime & Optimization, you will be developing technologies to advance the training and inferences of the AI models in autonomous driving systems
• Performing in-depth analysis and optimization to model training and deployment to achieve the state of art in performance and efficiency in autonomous driving
• Work across the entire AI framework/compiler stack (e.g. Torch, CUDA and TensorRT), support model development and prototype key deep learning algorithms
• Analyze the tradeoffs between performance, cost and energy for autonomous driving
• Collaborating closely with diverse groups in to influence the next-generation compute platform HW and SW design
• Research the latest model architectures, programming models and hardware
• This position is fully onsite in Fremont, at least 3 months