Machine Learning/AI Infrastructure Engineering Intern

About the role

About the Company

Netflix is a global entertainment service focused on delivering TV series, films, games, and other entertainment experiences to audiences around the world. The company combines storytelling, technology, data, and artificial intelligence to develop products and infrastructure that support its entertainment platform. The AI Platform team builds the infrastructure used by Netflix's machine learning and artificial intelligence systems. Its work spans large-scale model training, post-training and offline infrastructure, GPU-optimized inference, and model serving.

About the Role

Netflix is seeking a Machine Learning/AI Infrastructure Engineering Intern to join its AI Platform team for the Winter 2027 internship program. This opportunity is designed for PhD students interested in the intersection of machine learning and systems engineering. Rather than focusing exclusively on model development, interns will work on infrastructure that enables ML and AI systems to train, operate, and serve models efficiently at large scale. The role may involve distributed systems, ML training infrastructure, inference optimization, distributed serving, GPU systems, and model-system co-design. Interns will be embedded within a team and contribute to meaningful technical projects based on their research interests and skills.

Responsibilities

Contribute to infrastructure supporting large-scale machine learning and AI systems.

Work on distributed training and serving infrastructure.

Improve systems used for ML training and post-training workflows.

Contribute to offline ML infrastructure and data-processing systems.

Explore techniques for optimizing model inference and serving.

Work with GPU-optimized inference systems.

Investigate model-system co-design opportunities.

Develop and improve scalable systems for AI workloads.

Collaborate with modeling and infrastructure engineers.

Apply research knowledge to practical engineering challenges.

Analyze system performance and identify opportunities for optimization.

Develop reliable infrastructure components using appropriate systems and ML technologies.

Participate in technical discussions and engineering reviews.

Communicate research findings, technical decisions, and project results clearly.

Solve open-ended infrastructure problems involving machine learning systems at scale.

Qualifications

Currently enrolled in a PhD program in Computer Science, Distributed Systems, Systems, Networking, Machine Learning, Computer Engineering, or a related technical field.

Research or applied experience in one or more relevant areas.

Strong interest or experience in distributed systems.

Experience with distributed training or serving infrastructure is valuable.

Familiarity with ML training platforms, post-training infrastructure, or offline ML systems.

Experience with inference or serving optimization is relevant.

Interest in GPU-optimized inference or model-system co-design.

Strong proficiency in Python.

Strong written and verbal communication skills.

Curiosity and motivation to solve open-ended technical problems.

Ability to work effectively in a collaborative engineering environment.

Preferred Skills

Experience with systems programming languages is a strong advantage, including:

Go

C++

Rust

Familiarity with distributed computing and ML infrastructure technologies is also beneficial, including:

Ray

Kubernetes

Spark

ML training frameworks

ML serving systems

Distributed computing infrastructure

GPU-optimized inference systems

Candidates with experience spanning both systems engineering and machine learning are particularly well suited to the role.

Pay range and compensation package

Netflix states that its internship compensation is determined using market indicators along with factors such as the specific role, skills, experience, and location. The overall market range for Netflix internships is typically $40 to $85 per hour. Actual compensation may vary depending on the candidate's qualifications, role, and location.

Equal Opportunity Statement

Netflix is an equal-opportunity employer and is committed to building diverse and inclusive teams. The company states that it does not discriminate based on race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, military service, or other characteristics protected by applicable law. Netflix also aims to provide an inclusive interview experience and offers accommodations or adjustments for candidates who need support during the hiring process.