AI / ML Engineer - Remote

About the Role

Netflix is seeking a PhD-level Machine Learning/AI Infrastructure Engineering Intern to join the AI Platform team and help build the infrastructure that powers Netflix's machine learning and artificial intelligence systems. The team works across large-scale training platforms, post-training and offline infrastructure, GPU-optimized inference, and serving systems. This internship is designed for PhD researchers who enjoy working at the intersection of machine learning and systems rather than focusing exclusively on modeling. You will contribute to infrastructure challenges at Netflix scale, working in areas such as distributed systems, ML training and serving, inference optimization, and model-system codesign.

Responsibilities

• Contribute to infrastructure supporting Netflix's machine learning and AI systems.
• Work on large-scale distributed training and serving infrastructure.
• Contribute to ML training platforms, post-training systems, and offline infrastructure.
• Work on inference and serving optimization, including GPU-optimized inference.
• Explore model-system codesign at the intersection of machine learning and systems.
• Help solve open-ended infrastructure challenges at Netflix scale.
• Collaborate effectively within a technical research and engineering environment.

Required Qualifications

• Currently enrolled in a PhD program 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 areas: distributed systems; distributed training or serving infrastructure; ML training platforms; post-training or offline infrastructure; inference and serving optimization; GPU-optimized inference; model-system codesign.
• Proficiency in Python.
• Familiarity with distributed compute frameworks such as Ray, Kubernetes, or Spark and ML training/serving stacks.
• Strong written and verbal communication skills.
• Curious, self-motivated, and excited about solving open-ended infrastructure challenges at Netflix scale.

Preferred Qualifications

• Experience with systems programming languages such as Go, C++, or Rust.
• Publications or strong research alignment with systems-track venues such as OSDI, SOSP, or NSDI.
• Publications or research alignment with applied machine learning venues.
• Prior industry or internship experience in ML infrastructure.

Skills

• Machine learning infrastructure.
• AI infrastructure.
• Distributed systems.
• Distributed training and serving.
• ML training platforms.
• ML serving and inference.
• GPU-optimized inference.
• Model-system codesign.
• Distributed computing.
• Python programming.
• Distributed compute frameworks, including Ray, Kubernetes, and Spark.
• ML training and serving stacks.
• Systems engineering.
• Research and applied problem-solving.
• Open-ended technical problem-solving.
• Written and verbal communication.
• Curiosity and continuous learning.
• Self-motivation and initiative.

Pay

Netflix internships are paid, with the overall market range for Netflix internships typically $40/hour–$85/hour. Compensation may vary based on factors including the specific role, skills, experience, and location.

Benefits

• Health Plans.
• Mental Health support.
• 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.