Note: The job is a remote job and is open to candidates in USA. Netflix is a global entertainment service providing TV series, films, and games to members worldwide. The Machine Learning/AI Infrastructure Engineering Intern will work on AI Platform infrastructure, including large-scale training, post-training, offline systems, GPU-optimized inference, and serving, in collaboration with modeling teams.
Responsibilities
- The AI Platform team builds the infrastructure that Netflix's ML and AI systems run on, from large-scale training platforms and post-training/offline infrastructure to GPU-optimized inference and serving
- You'll work on infrastructure that's closely co-designed with modeling teams (model–system codesign), so this role suits PhD researchers who enjoy working at the intersection of systems and ML rather than pure modeling
Skills
- 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
- Curious, self-motivated, and excited about solving open-ended infrastructure challenges at Netflix scale
- Strong written and verbal communication skills
- Intended for students returning to school for at least one semester/quarter after the internship; conversion/return offers are based on business need and headcount, and are not guaranteed
- Publications or strong research alignment with systems-track venues (OSDI, SOSP, NSDI) or applied ML venues
- Prior industry or internship experience in ML infrastructure
- Based at our Los Gatos, CA headquarters, may be open to remote candidates
Benefits
- 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
- Life and Serious Injury Benefits
- Paid leave of absence programs
- Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off
- Full-time salaried employees are immediately entitled to flexible time off
- Location is flexible for this team, with remote candidates considered
Company Overview
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