Tech Stack

Description

You will invent novel hardware systems using Lightmatter's photonics technology, model performance of training and inference workloads, and collaborate with product and engineering teams to design reference platforms. Your work will directly shape cutting-edge AI infrastructure and be published at top conferences.

Requirements

• PhD in Computer Science, Electrical Engineering, or related field with 10+ years industry or research experience
• Solid background in ML systems research and performance modeling
• Hands-on experience with deep learning and LLM training/inference frameworks
• Academic publications in relevant venues
• Strong knowledge of AI compute and networking technologies

Responsibilities

• Stay up to date on latest ML research advancements
• Build tools to model performance of Passage-enabled systems for training and inference workloads
• Collaborate with product and solutions architecture teams to design reference platforms
• Publish academic papers at top industry conferences and journals
• Lead a small team of ML engineers