Machine Learning Systems Researcher

Join Lightmatter, a cutting-edge technology company focused on revolutionizing machine learning systems through silicon photonics. As a Machine Learning Systems Researcher, you will work closely with product, solutions architecture, and engineering teams to generate impactful performance analysis, create high-performance rack-scale designs, and publish cutting-edge ML systems research. You will have the opportunity to stay up to date on the latest advancements in machine learning research, build tools to model performance, and collaborate on designing compelling reference platforms for customers.

• Inventing novel hardware systems using Lightmatter technology and modeling their performance.
• Collaborating with product, solutions architecture, and engineering teams to generate impactful performance analysis.
• Publishing academic papers at top industry conferences and journals, and supporting the publication of whitepapers and blog posts.
• Adaptable and versatile, thriving in a high-speed, high-precision environment
• Academic publications in relevant journals and industry conferences
• Hands-on experience with machine learning / deep learning methods and extensive knowledge of Large Language Model training and inference frameworks
• Ability to independently own projects from conception to completion
• Exceptional skills in communicating complex research outcomes and technical concepts to partners and internal stakeholders, while embodying our value of speaking truth
• Must have knowledge of AI systems, including compute (GPUs, TPUs, etc.) and networking (Ethernet, Infiniband, NVLink, etc.) technologies, and their various topologies, paradigms, and trade-offs
• PhD in Computer Science, Electrical Engineering, or a related field
• Ability to work across research, product, and business functions, rolling up your sleeves to bridge gaps and accelerate outcomes, while demonstrating the core value of "We are one Lightmatter."
• Demonstrated ability to creatively problem-solve and apply first-principles thinking to generate novel ideas, particularly in ambiguous, evolving environments
• 2 - 5 years of industry and/or research experience in the field
• Solid background in Machine Learning systems research and experience with performance evaluation and performance modeling