Why This Role Stands Out
This hybrid role offers an exceptional opportunity to shape the future of AI hardware by leading the development of next-generation computing systems, perfect for experienced AI engineers eager to make a significant impact and grow their expertise in a collaborative, innovative environment. You'll thrive here if you're passionate about designing, training, and deploying advanced neural networks and have a knack for performance optimization, with the chance to work with a world-class team at a reputable global company. Apply today to join this exciting venture!
Quick Overview
Job Description
We are seeking a Lead AI Engineer to join a cutting-edge team building computers designed specifically for AI. Our customer brings together experts in computer architecture, ASIC design, advanced systems, and neural network compilers to build the next generation of computing. The team is actively working on compilers, neural networks, LLMs, and CNNs, and is looking for an experienced engineer to take on a Key Developer role within the ML & AI team.
Responsibilities Design, implement, and iterate on neural network architectures using PyTorch to achieve optimal performance on diverse tasks Train, validate, and fine-tune machine learning models using relevant datasets to ensure high accuracy and robustness Investigate and troubleshoot model performance issues, iterating on models and techniques to continuously improve results Analyze how models map onto Tenstorrent devices through compilation steps and kernels Identify gaps in functionality and performance, proposing innovative solutions to mitigate any issues Collaborate with cross-functional teams working on compilers, neural networks, LLMs, and CNNs Deploy neural networks for various applications, ensuring scalability and reliability Requirements 5+ years of experience in machine learning and AI engineering At least 1 year of relevant leadership experience Proficiency in Python programming with hands-on experience in PyTorch for developing and training deep learning models Expertise in designing, training, and deploying neural networks for various applications Understanding of machine learning fundamentals, including supervised and unsupervised learning techniques Background in investigating and troubleshooting model performance issues Capability to map models onto specialized AI hardware through compilation steps and kernels Strong English communication skills (B2 level or higher) Nice to have Experience with C++ and kernel programming Knowledge of GPU/AI-accelerator architectures
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