- A competitive salary range ($200,000 - $300,000+)
- An inclusive and supportive work environment
- The opportunity to shape the future of AI and ML technology
- Enhance LLM performance through hardware optimizations
- Lead quality assessments and infrastructure development for ML scalability
- Provide advice on hardware design focusing on ML optimizations
- Proficiency in software engineering and ML model optimization
- Experience in neural network training, especially LLMs
- Understanding of optimizing neural networks for hardware efficiency
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AI/ML Performance Engineer for LLM Acceleration - California, United States - Acceler8 Talent
Description
Join our cutting-edge team as an AI/ML Performance Engineer specializing in LLM Acceleration, where your skills will play a crucial role in shaping the future of artificial general intelligence (AGI) through innovative hardware solutions. Our goal is to develop the leading compute platform for AGI by designing hardware that enhances the speed, efficiency, and cost-effectiveness of AI. Unlike conventional methods that cater to all ML models, we concentrate solely on large language models (LLMs), enabling our hardware and software to achieve exceptional simplicity and performance.
Our Vision:
We are committed to transforming AGI by focusing exclusively on LLMs, understanding their distinct needs compared to other ML models. Our strategy allows us to streamline our hardware and software, making AI technologies faster, superior, and more economical. By dedicating ourselves to LLMs, we provide optimized solutions that surpass generic platforms, establishing new benchmarks in the AI sector.
About the Position:
Your objective will involve driving optimizations to ensure seamless and efficient operation of LLMs on state-of-the-art hardware. You will address challenges related to quality assessments, building distributed infrastructure for scalable training and inference, and offering strategic guidance on hardware optimizations for ML applications.
What's Included:
Primary Duties:
Qualifications:
This position, located in Mountain View and adopting a hybrid work arrangement, is ideal for individuals prepared to influence the fusion of AI and ML with hardware acceleration.
