Machine Learning Engineer Jobs at Netflix with Visa Sponsorship
Machine Learning Engineer jobs at Netflix involve building infrastructure at scale, and that ambition carries through to how the company hires for these roles. The company sponsors a range of visa types for technical talent, making it a realistic target if you're an international candidate with strong model development or ML systems experience.
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Get Access To All JobsAt 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.
We launched a new ad-supported tier in November 2022 and are building an in-house, world-class ad tech ecosystem to give our members more choices in how they enjoy Netflix. This tier lets us attract new members at a lower price point while creating a compelling path for advertisers to reach deeply engaged audiences.
Our Team
This role sits within the Ad Ranking org inside Ads Data Science and Engineering (DSE). Ad Ranking's key areas of focus span Identity Matching, Audience & Targeting, User Understanding, Relevance & Engagement Prediction, and Bidding & Pacing - the ML systems that decide which ad reaches which member, and when.
We're hiring a Machine Learning Scientist 6 to lead our user understanding charter. This person will leverage Netflix’s rich multimodal signals and LLM techniques to build a user-understanding foundation for the ads team. It will be used both as a feature foundation for ad targeting, ranking, and bidding. They'll also shape our 1P and 3P data strategy as the platform evolves, and will have latitude to partner across the broader Ads ML org.
Responsibilities
- Set the technical direction for user understanding by leveraging multimodal signals - from content, viewing behavior, and context.
- Shape and land Netflix's data strategy for a fast-growing team, partnering with privacy, legal, and platform engineering to build a data foundation that scales.
- Partner with the ranking, bidding & pacing teams to get user-understanding signals into production and drive downstream impact.
- Build rigorous online and offline evaluation frameworks to quantify the incremental value of new signals, representations, and models.
- Communicate technical strategy, trade-offs, and results to both technical and non-technical audiences, including senior leadership.
Qualifications
- Advanced degree (PhD or Master's) in Computer Science, Statistics, Mathematics, or a related quantitative field, or equivalent industry experience.
- 7+ years of industry experience building and shipping production ML systems at scale, with demonstrated staff/senior-staff-level scope and impact.
- Track record building user or audience understanding systems - embeddings, representation learning, identity resolution, or similar - ideally in a monetization or ads context.
- Hands-on experience applying LLM to user modeling, content understanding, or recommendation, with good judgment on where these approaches beat traditional methods.
- Influence 1P/3P data strategy, privacy-aware data usage, or identity/targeting infrastructure is a strong plus.
- A track record of setting technical direction and influencing roadmap across teams; experience as a vertical or xfn technical lead is a strong plus.
- Proficiency in Python, Scala, or Java, and experience prototyping and deploying models on large-scale production data.
- Strong business acumen and the ability to translate technical results into business impact.
- Excellent communication and cross-functional collaboration skills.
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 $600,000.00 - $1,066,000.00. This compensation range will vary based on location.
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.
Job is open for no less than 7 days and will be removed when the position is filled.
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.
We launched a new ad-supported tier in November 2022 and are building an in-house, world-class ad tech ecosystem to give our members more choices in how they enjoy Netflix. This tier lets us attract new members at a lower price point while creating a compelling path for advertisers to reach deeply engaged audiences.
Our Team
This role sits within the Ad Ranking org inside Ads Data Science and Engineering (DSE). Ad Ranking's key areas of focus span Identity Matching, Audience & Targeting, User Understanding, Relevance & Engagement Prediction, and Bidding & Pacing - the ML systems that decide which ad reaches which member, and when.
We're hiring a Machine Learning Scientist 6 to lead our user understanding charter. This person will leverage Netflix’s rich multimodal signals and LLM techniques to build a user-understanding foundation for the ads team. It will be used both as a feature foundation for ad targeting, ranking, and bidding. They'll also shape our 1P and 3P data strategy as the platform evolves, and will have latitude to partner across the broader Ads ML org.
Responsibilities
- Set the technical direction for user understanding by leveraging multimodal signals - from content, viewing behavior, and context.
- Shape and land Netflix's data strategy for a fast-growing team, partnering with privacy, legal, and platform engineering to build a data foundation that scales.
- Partner with the ranking, bidding & pacing teams to get user-understanding signals into production and drive downstream impact.
- Build rigorous online and offline evaluation frameworks to quantify the incremental value of new signals, representations, and models.
- Communicate technical strategy, trade-offs, and results to both technical and non-technical audiences, including senior leadership.
Qualifications
- Advanced degree (PhD or Master's) in Computer Science, Statistics, Mathematics, or a related quantitative field, or equivalent industry experience.
- 7+ years of industry experience building and shipping production ML systems at scale, with demonstrated staff/senior-staff-level scope and impact.
- Track record building user or audience understanding systems - embeddings, representation learning, identity resolution, or similar - ideally in a monetization or ads context.
- Hands-on experience applying LLM to user modeling, content understanding, or recommendation, with good judgment on where these approaches beat traditional methods.
- Influence 1P/3P data strategy, privacy-aware data usage, or identity/targeting infrastructure is a strong plus.
- A track record of setting technical direction and influencing roadmap across teams; experience as a vertical or xfn technical lead is a strong plus.
- Proficiency in Python, Scala, or Java, and experience prototyping and deploying models on large-scale production data.
- Strong business acumen and the ability to translate technical results into business impact.
- Excellent communication and cross-functional collaboration skills.
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 $600,000.00 - $1,066,000.00. This compensation range will vary based on location.
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.
Job is open for no less than 7 days and will be removed when the position is filled.
See all Machine Learning Engineer Jobs at Netflix
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Engineer Jobs at Netflix.
Get Access To All JobsTips for Finding Machine Learning Engineer Jobs at Netflix
Align your portfolio with Netflix's ML stack
Netflix engineering blog posts detail the systems behind their recommendation engine, A/B testing platform, and content encoding pipelines. Framing your portfolio around similar domains, such as ranking models or real-time inference, signals direct relevance to their open ML roles.
Target roles that clear the specialty occupation bar
USCIS requires H-1B roles to qualify as specialty occupations requiring a specific bachelor's degree or higher. ML Engineer positions at Netflix typically map to computer science, statistics, or a related technical field, so ensure your degree field is explicitly documented in your resume and application materials.
Use Migrate Mate to filter Netflix ML openings by visa type
Netflix posts ML roles across multiple teams with different sponsorship profiles. Use Migrate Mate to surface active Netflix listings filtered by the visa types you need, so you're applying to positions where sponsorship is already confirmed rather than guessing from a standard job board.
Prepare for Netflix's systems design interview format
Netflix ML interviews typically include a systems design round focused on building scalable recommendation or personalization infrastructure. Preparing examples where you've designed or optimized production ML pipelines strengthens your case and moves you faster to the offer stage where sponsorship discussions happen.
Request your LCA details before accepting an offer
Before signing, ask your recruiter to confirm the job location listed on the Labor Condition Application filed with DOL. Netflix operates across multiple offices, and the LCA must reflect your actual work site or remote arrangement to avoid compliance issues after you start.
Plan around the H-1B cap if you're on OPT
If you're currently on F-1 OPT, Netflix would need to file your H-1B cap petition in April for an October 1 start date. STEM OPT extensions give you up to 24 additional months of work authorization, so timing your Netflix application to maximize that window reduces gaps in your authorization.
Frequently Asked Questions
Does Netflix sponsor H-1B visas for Machine Learning Engineers?
Yes, Netflix sponsors H-1B visas for Machine Learning Engineer roles. ML engineering positions at Netflix typically qualify as specialty occupations under USCIS criteria, given the degree requirements in computer science, statistics, or a closely related field. Netflix handles sponsorship through its internal immigration team, so the process is well-established for technical hires rather than being managed ad hoc.
Which visa types does Netflix commonly sponsor for Machine Learning Engineer roles?
Netflix sponsors several visa categories for ML engineering talent, including H-1B, E-3 visa for Australian citizens, TN visa for Canadian and Mexican nationals, and F-1 OPT and CPT for students. For longer-term pathways, Netflix also supports Green Card sponsorship through EB-2 and EB-3 classifications, making it a viable option if you're thinking beyond your first work visa.
What qualifications does Netflix expect for Machine Learning Engineer roles?
Netflix ML Engineer roles typically require a bachelor's or advanced degree in computer science, mathematics, or statistics, along with hands-on experience building production ML systems rather than purely research work. Familiarity with large-scale recommendation systems, real-time inference pipelines, or experimentation platforms aligns well with Netflix's known technical priorities. Industry experience matters more at Netflix than academic credentials alone.
How do I apply for Machine Learning Engineer jobs at Netflix?
You can find and filter active Netflix Machine Learning Engineer openings by visa type on Migrate Mate, which lets you confirm sponsorship availability before applying. When applying directly, tailor your resume to highlight production ML experience over research projects, since Netflix engineering interviews focus heavily on systems thinking and real-world model deployment rather than theoretical knowledge.
How do I plan my timeline if Netflix sponsors my visa?
If you're on F-1 OPT, STEM OPT gives you up to 24 additional months of work authorization, which gives Netflix time to file an H-1B cap petition by the April deadline for an October 1 start. For E-3 or TN holders, Netflix can typically file outside the cap with shorter lead times. Confirm your start date and visa category with Netflix's immigration team early so USCIS processing timelines don't delay your onboarding.