AI ML Engineer Jobs at Netflix with Visa Sponsorship
AI ML Engineer roles at Netflix sit at the intersection of large-scale recommendation systems, content personalization, and generative AI research. Netflix has a strong track record of sponsoring international talent across multiple visa categories for this function, making it a realistic target for skilled engineers who need work authorization.
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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.
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.

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.
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 ML Engineer Jobs at Netflix Jobs
Align your portfolio to Netflix's ML stack
Netflix publicly shares engineering work on recommendation systems, A/B testing infrastructure, and large-scale model serving. Tailor your portfolio to these domains before applying. Interviewers assess domain fit alongside technical depth.
Time H-1B applications around the cap lottery
If you need H-1B sponsorship and aren't cap-exempt, Netflix must register you in the April lottery. Coordinate your offer timeline so your start date accommodates a potential October 1 status change, not an earlier one.
Prepare your specialty occupation documentation early
USCIS requires evidence that AI ML Engineer roles meet specialty occupation standards. Gather transcripts, degree evaluations, and publications ahead of time. A computer science or statistics degree with ML coursework strengthens the petition significantly.
Use Migrate Mate to filter AI ML Engineer roles at Netflix
Not all Netflix job postings surface easily on general boards. Use Migrate Mate to browse AI ML Engineer openings at Netflix filtered by visa type, so you're only applying to roles aligned with your sponsorship eligibility.
Request a PERM timeline discussion for long-term planning
If your goal is a Green Card, ask Netflix's immigration team about PERM labor certification timelines during the offer stage. AI ML Engineers from certain countries face significant backlogs, and earlier sponsorship initiation meaningfully affects your path.
AI ML Engineer at Netflix jobs are hiring across the US. Find yours.
Find AI ML Engineer at Netflix JobsFrequently Asked Questions
Does Netflix sponsor H-1B visas for AI ML Engineers?
Yes, Netflix sponsors H-1B visas for AI ML Engineers. If you're subject to the H-1B cap, Netflix must register you in the USCIS annual lottery, which opens in March for an October 1 start date. Cap-exempt candidates, such as those transferring from qualifying research institutions, can file outside the lottery window.
How do I apply for AI ML Engineer jobs at Netflix?
Applications go through Netflix's careers portal. Roles in AI and ML at Netflix typically require demonstrating applied experience with recommendation systems, deep learning, or large-scale model deployment. Migrate Mate lets you browse current AI ML Engineer openings at Netflix filtered by the visa types they sponsor, which helps you focus your applications on roles matching your authorization status.
Which visa types does Netflix commonly sponsor for AI ML Engineers?
Netflix sponsors H-1B, E-3, TN, F-1 OPT, F-1 CPT, J-1, and EB-2/EB-3 immigrant visas for this role. E-3 is available exclusively to Australian citizens and skips the H-1B lottery entirely. TN applies to Canadian and Mexican nationals under USMCA. F-1 OPT and CPT allow students to work while their longer-term sponsorship is arranged.
What qualifications does Netflix expect for AI ML Engineer roles?
Netflix typically looks for a graduate degree in computer science, statistics, or a related quantitative field, combined with hands-on experience building and deploying ML models at scale. Familiarity with personalization systems, A/B experimentation, and distributed computing frameworks is relevant. Published research or open-source contributions in ML can strengthen your candidacy, particularly for senior-level positions.
How long does the visa sponsorship process take for an AI ML Engineer at Netflix?
Timeline depends heavily on visa type. H-1B cases filed under cap have a fixed October 1 start date, so the process spans roughly six months from lottery registration to authorization. E-3 and TN petitions move faster, often resolving within weeks. EB-2 and EB-3 Green Card sponsorship involves PERM labor certification with DOL, which typically adds a year or more before I-140 filing.
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