Job Qualification
Graduate with a MS, or Ph.D. degree in Computer Science, Computer Engineering, Applied Math, or related field.
Can work independently, define project goals and scope, and lead your own development effort.
Strong Python or C++/C programming and software design skills, including debugging, performance analysis, and test design.
Experience with Deep Learning Frameworks such as PyTorch, TensorFlow, and MXNet
Experience with model acceleration techniques such as deep learning quantization, model pruning, and model distillation.
Ways to stand out from the crowd:
Experience with numerical methods
Knowledge of computer architecture
Experience with AI compilers
Experience in model deployment within the autonomous driving industry
Experience deploying LLMs on edge devices
Job Description
We are looking for an experienced AI/ML engineer passionate about deploying AI inference and end to end enablement, AI framework integration, model accuracy, and performance analysis and tuning. You might be an ideal candidate if you are seeking to develop high quality, innovative, and scalable software that enables state of the art AI inference models to run efficiently and accurately on the BST Intelligence processors.
Responsibilities:
Contribute to deep learning infrastructure, data pipelines, tools and workflows that lay the foundation for building AI at scale.
Writing software to deploy AI models and pipelines in real time applications (inference).
Apply low precision inference, quantization, and compression of DNNs.
Continuously improve inference latency, accuracy and power consumption of DNNs.
Stay up to date with the latest research and innovations in deep learning, implement and experiment with new ideas
Job Location: 2290 N 1st. St. STE100 San Jose, CA 95131
