Role OverviewThe AI Platform team builds the infrastructure that Netflix's ML and AI systems run on. You'll work on infrastructure that's closely co-designed with modeling teams, so this role suits PhD researchers who enjoy working at the intersection of systems and ML rather than pure modeling.
What You Will Do
You'll work on infrastructure projects such as large-scale training platforms, post-training/offline infrastructure, and GPU-optimized inference and serving.
Why It Might Be a Fit
You'll be a good fit if you're a curious, self-motivated PhD researcher with experience in distributed systems, ML training platforms, and inference and serving optimization, and you're excited about solving open-ended infrastructure challenges at Netflix scale.
Requirements
- Currently enrolled student pursuing a PhD in Computer Science, Distributed Systems, Systems, Networking, Machine Learning, Computer Engineering, or a related field
- Research or applied experience in one or more of the following: Distributed systems, distributed training/serving infrastructure, ML training platforms, post-training or offline infrastructure, Inference and serving optimization, GPU-optimized inference, Model–system codesign
- Proficiency in Python; experience with systems languages (Go, C++, or Rust) is a strong plus
- Familiarity with distributed compute frameworks (e.g., Ray, Kubernetes, Spark) and ML training/serving stacks
- Strong written and verbal communication skills
Benefits
- Paid internship
- Comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits
- Paid leave of absence programs
- 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off
- Flexible time off
]]>