ML Engineer Jobs at Netflix with Visa Sponsorship
Netflix builds its machine learning infrastructure around researchers and engineers who move fluidly between recommendation systems, content personalization, and large-scale experimentation. The company sponsors a range of work visas for ML Engineers and has an established process for supporting international candidates through the offer and filing stages.
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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 ML Engineer Jobs at Netflix Jobs
Align your portfolio to Netflix's ML stack
Netflix's ML work centers on recommendation systems, A/B experimentation platforms, and real-time inference at scale. Tailor your GitHub projects and system design examples to these areas before applying, not after you get the call.
Target roles that match your visa category
Netflix sponsors H-1B, E-3, TN, and F-1 OPT across ML functions, but not every role listing explicitly states this. Check whether the position is research-oriented or production-focused, since specialty occupation classification matters for H-1B petitions USCIS reviews.
Start OPT paperwork well before an offer lands
If you're on F-1, your designated school official needs lead time to issue a new I-20 for OPT. File your USCIS Form I-765 at least 90 days before your program end date so authorization is in hand when Netflix moves to onboarding.
Clarify sponsorship scope during the offer stage
Netflix has in-house immigration counsel, but you should confirm whether they cover green card sponsorship under EB-2 or EB-3 in addition to H-1B. Some engineering teams move faster on PERM than others, and understanding this affects your long-term planning.
Use Migrate Mate to surface Netflix ML openings that fit your visa
Netflix posts ML Engineer roles across multiple teams with different sponsorship postures. Search Migrate Mate to filter open positions by visa type so you're applying to roles where your specific status is already supported.
Prepare a technical narrative that bridges your degree and the role
USCIS scrutinizes whether an ML Engineer position constitutes a specialty occupation. Your degree field and the specific technical requirements of the Netflix role need to map clearly, so document that connection before your employer files Form I-129.
ML Engineer at Netflix jobs are hiring across the US. Find yours.
Find ML Engineer at Netflix JobsFrequently Asked Questions
Does Netflix sponsor H-1B visas for ML Engineers?
Yes, Netflix sponsors H-1B visas for ML Engineers. The company has established immigration support through in-house legal resources and sponsors across multiple visa categories for this function. Because H-1B requires demonstrating specialty occupation status, your application materials should clearly connect your degree field to the specific technical requirements of the role you're being hired into.
Which visa types does Netflix commonly sponsor for ML Engineer roles?
Netflix sponsors H-1B, E-3 for Australian citizens, TN for Canadian and Mexican nationals, F-1 OPT and CPT for students, J-1, and immigrant visa pathways including EB-2 and EB-3. ML Engineer roles typically qualify under specialty occupation requirements across these categories, but the right visa depends on your nationality, educational background, and career stage.
What qualifications and experience does Netflix expect from ML Engineer candidates?
Netflix typically looks for a graduate degree in machine learning, statistics, computer science, or a related quantitative field, combined with hands-on experience building production ML systems. Familiarity with large-scale recommendation or ranking systems, experimentation frameworks, and real-time inference pipelines is particularly relevant given how Netflix's ML platform is structured across its product and content teams.
How do I apply for ML Engineer jobs at Netflix?
Browse open ML Engineer roles on Migrate Mate to filter by visa sponsorship type and find positions that fit your work authorization. Once you identify a role, apply through Netflix's careers portal with a resume that highlights production ML experience and any systems-level work relevant to recommendation, personalization, or experimentation at scale. Netflix's process typically includes a recruiter screen, technical interviews, and a systems design round.
How do I plan the H-1B filing timeline if I receive an offer from Netflix?
The H-1B cap lottery opens in March for an October 1 start date, so timing your offer and acceptance accordingly is critical. If you're already in valid H-1B status with another employer, Netflix can file an H-1B transfer with USCIS that allows you to start once the petition is received, without waiting for the new cap year. Cap-exempt situations, such as transitioning from F-1 OPT, follow different timelines.
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