Lightmatter
Machine Learning Systems Researcher
About this role
Lightmatter seeks a Machine Learning Systems Researcher to innovate hardware systems leveraging silicon photonics technology for AI data centers. You'll model performance of Passage-enabled systems for training and inference workloads, collaborate across product and engineering teams, and publish cutting-edge ML systems research.
What you'll do
- Monitor latest advancements in machine learning research and apply insights to systems design
- Develop performance modeling tools for Passage-enabled systems running modern AI workloads
- Design reference platforms with product and solutions architecture teams for customer deployment
- Serve as ML expert guiding technical decisions across the organization
- Publish academic papers at top conferences and support whitepapers and marketing materials
- Own projects independently from conception through completion
What they're looking for
- Machine learning systems research and performance modeling
- Deep learning frameworks and large language model training/inference
- AI compute architectures (GPUs, TPUs) and networking technologies
- Performance evaluation and benchmarking methodologies
- First-principles problem-solving and creative ideation
- Technical communication to diverse stakeholders
- Cross-functional collaboration across research, product, and engineering
- Python or similar systems programming languages
Benefits
- Competitive base salary ($186K-$240K) plus equity grants
- Comprehensive health coverage (medical, dental, vision)
- Retirement savings matching program
- Generous paid time off including family leave
- Flexible hybrid workplace model
- Training and development opportunities
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Lightmatter
Lightmatter builds silicon photonics-based optical interconnect products and AI data center infrastructure powered by advanced photonic technologies. The company is hiring hardware validation engineers, mechanical designers, and mixed-signal validation engineers to design test systems, verify high-speed electro-optic links, develop server chassis platforms, and optimize photonic communication circuits.
- Website
- lightmatter.com
Likely interview questions
- Walk us through a performance modeling or simulation project you've built for ML systems. How did you validate its accuracy against real hardware?
- Describe your experience with Large Language Model training and inference frameworks. Which have you worked with most deeply, and what are the key performance bottlenecks you've analyzed?