Principal Machine Learning Infrastructure Researcher
$300k - $350k • Mountain View, CA
Posted 1mo ago
Job Location
Mountain View, CA
Tech Stack
Remote Work Policy
On-site
Categories
Machine Learning Engineer
About the job
Lightmatter is seeking a Principal Machine Learning Infrastructure Researcher to join our Machine Learning team. This team is focused on inventing novel hardware systems using Lightmatter technology and modeling the performance of Lightmatter-enabled systems on both training and inference workloads. This is primarily a creative role where you need to think outside the box to push the boundaries of systems research with the power of silicon photonics at your fingertips. This role will work closely with our product, solutions architecture, and engineering teams to generate impactful performance analysis, create high-performance rack-scale designs, and publish cutting-edge ML systems research.
Responsibilities
- Stay up to date on the latest advancements in Machine Learning research.
- Build tools to model the performance of Passage-enabled systems for training and inference workloads of AI models.
- Collaborate with product and solutions architecture teams to design reference platforms for customers.
- Serve as the Machine Learning expert in discussions.
- Publish academic papers at top industry conferences and journals, and support the publication of whitepapers and blog posts.
- Lead a small team of Machine Learning engineers.
Requirements
- PhD in Computer Science, Electrical Engineering, or a related field.
- At least 10 years of industry or research experience in Machine Learning systems research.
- Experience with performance evaluation and performance modeling.
- Hands-on experience with machine learning/deep learning methods.
- Extensive knowledge of Large Language Model training and inference frameworks.
- Academic publications in relevant journals and industry conferences.
- Strong knowledge of AI systems, including compute (GPUs, TPUs) and networking (Ethernet, Infiniband, NVLink) technologies, their topologies, paradigms, and trade-offs.
- Proven track record leading a team to deliver published results.
Benefits
- Competitive compensation
- Comprehensive Health Care Plan (Medical, Dental & Vision)
- Retirement Savings Matching Program
- Life Insurance (Basic, Voluntary & AD&D)
- Generous Time Off (Vacation, Sick & Public Holidays)
- Paid Family Leave
- Short Term & Long Term Disability
- Training & Development
- Commuter Benefits
- Flexible, hybrid workplace model
- Equity grants