AI Data Engineer Jobs at Netflix with Visa Sponsorship
Netflix hires AI Data Engineers to build and scale the data infrastructure behind its recommendation systems, content analytics, and machine learning platforms. The company has a consistent track record of sponsoring work visas for this function, supporting candidates across multiple visa categories from initial hire through long-term residency pathways.
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INTRODUCTION
At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.
THE TEAM
The Studio Media Algorithms team is at the forefront of algorithmic innovation to enhance and support the creation of Netflix’s entertainment content, including games. In this role, you will be embedded within this team while collaborating very closely with a specialized Games Studio R&D team. This incubation-style team is chartered to lead our investments in building new kinds of games leveraging emerging technologies to support our creators and reach player audiences in new ways.
THE ROLE
We are looking for a Machine Learning Engineer with a focus on MLOps, deployment, and performance optimization to help bridge the gap between research and production in the gaming space. You will work cross-functionally with games technical directors, designers, and scientists to ensure that novel AI-driven game concepts can be deployed efficiently across a variety of hardware environments.
IN THIS ROLE, YOU WILL
- Build and maintain MLOps pipelines: Develop robust CI/CD for ML, model registries, and automated deployment workflows to support rapid iteration.
- Optimize for performance: Profile and benchmark models across cloud GPUs and edge devices (e.g., Nsight, PyTorch Profiler) to identify bottlenecks and implement hardware acceleration.
- Scale deployment: Design and implement model deployment strategies for both Cloud and Edge environments, ensuring efficient, low-latency execution in game runtimes.
- Enhance model efficiency: Apply precision tuning and quantization techniques to meet latency, cost, and memory constraints without significant quality loss.
- Collaborate on integration: Work with game engineers to integrate ML models into game engine pipelines and APIs.
ABOUT YOU
- MLOps & Deployment Expertise: Proven experience with model registries, containerization, and building end-to-end CI/CD pipelines for machine learning. Experience productionizing ML models in the cloud (e.g., AWS and SageMaker endpoints), including scaling, monitoring, and working closely with platform/infra teams.
- Hardware Profiling & Acceleration: Experience in profiling and optimizing ML inference on GPUs, with knowledge of CUDA-based runtimes and tools (e.g., Nsight, cuDNN, TensorRT, ONNX Runtime).
- Compiler & Runtime Knowledge: Familiarity with graph compiler optimization and tools like MLIR or LLVM.
- Framework Proficiency: Extensive experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
- Strong Software Engineering: Ability to develop high-quality, maintainable code and integrate complex algorithmic solutions into production systems.
- Passion for Games: A strong interest in how technology enables joy and innovation in the video game industry.
BONUS EXPERIENCE
- Hands-on experience deploying ML models on edge, such as iOS or Android devices, including model optimization and hardware-aware inference.
- Experience in game development and familiarity with game engines (e.g., Unity, Unreal).
- Experience in model distillation, pruning, or other model compression techniques.
COMPENSATION
Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $466,000.00 - $750,000.00.
Netflix provides 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. We also offer 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. See more details about our Benefits here.
Netflix is a unique culture and environment. Learn more here. Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.
We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

INTRODUCTION
At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.
THE TEAM
The Studio Media Algorithms team is at the forefront of algorithmic innovation to enhance and support the creation of Netflix’s entertainment content, including games. In this role, you will be embedded within this team while collaborating very closely with a specialized Games Studio R&D team. This incubation-style team is chartered to lead our investments in building new kinds of games leveraging emerging technologies to support our creators and reach player audiences in new ways.
THE ROLE
We are looking for a Machine Learning Engineer with a focus on MLOps, deployment, and performance optimization to help bridge the gap between research and production in the gaming space. You will work cross-functionally with games technical directors, designers, and scientists to ensure that novel AI-driven game concepts can be deployed efficiently across a variety of hardware environments.
IN THIS ROLE, YOU WILL
- Build and maintain MLOps pipelines: Develop robust CI/CD for ML, model registries, and automated deployment workflows to support rapid iteration.
- Optimize for performance: Profile and benchmark models across cloud GPUs and edge devices (e.g., Nsight, PyTorch Profiler) to identify bottlenecks and implement hardware acceleration.
- Scale deployment: Design and implement model deployment strategies for both Cloud and Edge environments, ensuring efficient, low-latency execution in game runtimes.
- Enhance model efficiency: Apply precision tuning and quantization techniques to meet latency, cost, and memory constraints without significant quality loss.
- Collaborate on integration: Work with game engineers to integrate ML models into game engine pipelines and APIs.
ABOUT YOU
- MLOps & Deployment Expertise: Proven experience with model registries, containerization, and building end-to-end CI/CD pipelines for machine learning. Experience productionizing ML models in the cloud (e.g., AWS and SageMaker endpoints), including scaling, monitoring, and working closely with platform/infra teams.
- Hardware Profiling & Acceleration: Experience in profiling and optimizing ML inference on GPUs, with knowledge of CUDA-based runtimes and tools (e.g., Nsight, cuDNN, TensorRT, ONNX Runtime).
- Compiler & Runtime Knowledge: Familiarity with graph compiler optimization and tools like MLIR or LLVM.
- Framework Proficiency: Extensive experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
- Strong Software Engineering: Ability to develop high-quality, maintainable code and integrate complex algorithmic solutions into production systems.
- Passion for Games: A strong interest in how technology enables joy and innovation in the video game industry.
BONUS EXPERIENCE
- Hands-on experience deploying ML models on edge, such as iOS or Android devices, including model optimization and hardware-aware inference.
- Experience in game development and familiarity with game engines (e.g., Unity, Unreal).
- Experience in model distillation, pruning, or other model compression techniques.
COMPENSATION
Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $466,000.00 - $750,000.00.
Netflix provides 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. We also offer 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. See more details about our Benefits here.
Netflix is a unique culture and environment. Learn more here. Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.
We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
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Get Access To All JobsTips for Finding AI Data Engineer Jobs at Netflix Jobs
Align your portfolio to Netflix's data culture
Netflix publishes engineering blog posts detailing their data platform architecture, including tools like Apache Spark, Flink, and their internal Metaflow framework. Referencing these specifically in your resume and interviews signals genuine familiarity with their stack, not generic data engineering experience.
Target roles with active LCA filings
Before applying, search the DOL's Labor Condition Application disclosure data to confirm Netflix has recently filed LCAs for AI Data Engineer positions. Active filings indicate open headcount with sponsorship already in motion, not just a standing job post.
Clarify your visa category early in conversations
Netflix sponsors several nonimmigrant categories, so recruiters need to know upfront whether you're on OPT, H-1B, TN, or E-3. Flagging your status in your cover letter removes ambiguity and helps their immigration team assess timelines before an offer is extended.
Understand OPT cap-gap timing if you're on F-1
If you're completing OPT and Netflix selects you in the H-1B lottery, your work authorization continues automatically during the cap-gap period until October 1. Confirm your I-20 end date and OPT expiration with your DSO so Netflix's legal team can plan the petition window accurately.
Use Migrate Mate to filter Netflix AI Data Engineer openings by visa type
Netflix posts AI Data Engineer roles across multiple teams with varying sponsorship scopes. Migrate Mate lets you filter those openings by the visa categories you hold, so you're applying to positions already confirmed as sponsorship-eligible rather than guessing from generic job descriptions.
Request PERM timeline clarity before accepting an offer
Netflix's EB-2 and EB-3 green card pathways require PERM labor certification through the DOL, a process that can run six months to over a year before USCIS sees the petition. Ask the recruiting team which green card track is standard for the role and where they typically initiate that process.
AI Data Engineer at Netflix jobs are hiring across the US. Find yours.
Find AI Data Engineer at Netflix JobsFrequently Asked Questions
Does Netflix sponsor H-1B visas for AI Data Engineers?
Yes, Netflix sponsors H-1B visas for AI Data Engineer roles. Because the H-1B is subject to an annual lottery capped at 85,000 slots, your selection isn't guaranteed, so Netflix's immigration team typically coordinates petitions well ahead of the April filing window. If you're already on a valid H-1B with another employer, a transfer to Netflix avoids the lottery entirely.
How do I apply for AI Data Engineer jobs at Netflix?
Apply directly through Netflix's careers site, where AI Data Engineer roles are listed by team and location. Tailor your application to highlight large-scale data pipeline experience, machine learning infrastructure, and familiarity with the tools Netflix uses publicly, such as Apache Spark and Python-based orchestration frameworks. You can also browse and filter Netflix's open AI Data Engineer positions by visa type on Migrate Mate.
Which visa types does Netflix commonly use for AI Data Engineers?
Netflix sponsors H-1B, E-3, TN, J-1, and F-1 OPT and CPT for AI Data Engineer roles, along with EB-2 and EB-3 immigrant visa pathways for longer-term residency. Australian citizens often pursue the E-3, which has no lottery and renews in two-year increments. Canadian and Mexican nationals in qualifying technical roles may qualify under the TN category with faster processing than the H-1B.
What qualifications does Netflix expect for AI Data Engineer roles?
Netflix's AI Data Engineer roles typically require a bachelor's or master's degree in computer science, data engineering, or a related field, along with hands-on experience building distributed data systems at scale. Familiarity with streaming architectures, ML feature pipelines, and tools like Spark, Kafka, or Flink is expected. Roles at Netflix place significant weight on engineering judgment and the ability to work autonomously within a high-autonomy culture.
How long does the visa sponsorship process take when joining Netflix?
Timeline depends on the category. H-1B petitions filed under regular processing take three to five months after the October 1 start date, though Netflix may elect premium processing for a faster USCIS adjudication within 15 business days. E-3 and TN approvals can move faster, sometimes within weeks. PERM-based Green Card sponsorship through EB-2 or EB-3 adds a separate multi-stage process that typically begins after you've been with the company for some time.
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