Distributed Systems Engineer Jobs in USA with Visa Sponsorship
Distributed systems engineers are among the most consistently sponsored roles in U.S. tech. H-1B visa approval rates for software infrastructure roles run high, and many employers sponsor from day one. This page shows open roles that include visa sponsorship. For detailed occupation requirements, see the O*NET profile.
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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 offer our members more choices in consuming their content. Our new tier allows us to attract new members at a lower price point while also creating a compelling path for advertisers to reach deeply engaged audiences.
Our Team
The Decisioning & Optimization engineering team sits within the Ad Serving & Decisioning org at Netflix Ads. We own the systems that power real-time ad decisioning, delivering relevant, high-quality ads while balancing revenue goals, advertiser outcomes, and member experience. Our work spans ML model serving infrastructure, ranking and scoring, auction mechanics, budget and pacing systems, and goal-based delivery optimization along with podding, traffic shaping models, and more.
We are looking for a strong systems engineer to build and scale the core infrastructure behind ads optimization at Netflix. You will work across the stack from model serving to auction execution to pacing, shipping production systems that directly impact revenue and advertiser outcomes.
- Build and evolve the real-time ad decisioning path: ranking, scoring, bidding, and pacing under strict latency and throughput constraints
- Develop and operate ML model serving infrastructure supporting dozens of concurrent hot-path models with sub-20ms P99 inference, including model routing, lifecycle management, fallback tiers, and calibration serving
- Partner with Science and Platform teams to productionize models and deploy algorithms into the serving stack
- Build simulation and testing frameworks to enable offline validation of marketplace changes before live rollout
- Implement and improve real-time pacing systems that drive budget delivery accuracy across campaign lifetimes
- Contribute to goal-based delivery optimization: dynamic allocation of budget and inventory across demand channels
- Build reusable components and clean interfaces that improve developer velocity across the team
- Participate in operational excellence: reliability, observability, deployment automation, and incident response across the optimization stack
Skills & Experience We're Seeking
- 7+ years building distributed systems and backend services at scale
- Ads domain experience (2+ years): worked on ad serving, delivery, or marketplace systems
- Experience with ML model serving infrastructure: real-time inference, model deployment pipelines, feature hydration, fallback strategies
- Built or worked on core ad tech systems: ad servers, bidders, pacers, or ranking and scoring components
- Built APIs and backend services that integrate across a multi-team platform
- Understanding of ad serving concepts: inventory management, frequency capping, member ad experience quality, and supply-demand dynamics
- Comfortable working at the intersection of engineering and data science, productionizing ML models into low-latency serving paths
- Ability to operate in an environment that is a mix of big-tech scale and startup speed
Nice to Haves
- Experience with auction mechanics: first-price, second-price, reserve pricing, bid shading
- Experience building multi-stage ranking systems (retrieval, scoring, reranking), podding and ad break planning
- Built or improved budget pacing and delivery control systems
- Familiar with CTV constraints: server-side ad insertion, live event ad serving at scale
- Experience with experimentation infrastructure: A/B testing, holdout groups, marketplace experiments
- Built simulation or counterfactual testing platforms for marketplace or auction systems
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 $388,000.00 - $619,000.00.
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.
Netflix is a unique culture and environment.
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.
We launched a new ad-supported tier in November 2022 and are building an in-house world-class ad tech ecosystem to offer our members more choices in consuming their content. Our new tier allows us to attract new members at a lower price point while also creating a compelling path for advertisers to reach deeply engaged audiences.
Our Team
The Decisioning & Optimization engineering team sits within the Ad Serving & Decisioning org at Netflix Ads. We own the systems that power real-time ad decisioning, delivering relevant, high-quality ads while balancing revenue goals, advertiser outcomes, and member experience. Our work spans ML model serving infrastructure, ranking and scoring, auction mechanics, budget and pacing systems, and goal-based delivery optimization along with podding, traffic shaping models, and more.
We are looking for a strong systems engineer to build and scale the core infrastructure behind ads optimization at Netflix. You will work across the stack from model serving to auction execution to pacing, shipping production systems that directly impact revenue and advertiser outcomes.
- Build and evolve the real-time ad decisioning path: ranking, scoring, bidding, and pacing under strict latency and throughput constraints
- Develop and operate ML model serving infrastructure supporting dozens of concurrent hot-path models with sub-20ms P99 inference, including model routing, lifecycle management, fallback tiers, and calibration serving
- Partner with Science and Platform teams to productionize models and deploy algorithms into the serving stack
- Build simulation and testing frameworks to enable offline validation of marketplace changes before live rollout
- Implement and improve real-time pacing systems that drive budget delivery accuracy across campaign lifetimes
- Contribute to goal-based delivery optimization: dynamic allocation of budget and inventory across demand channels
- Build reusable components and clean interfaces that improve developer velocity across the team
- Participate in operational excellence: reliability, observability, deployment automation, and incident response across the optimization stack
Skills & Experience We're Seeking
- 7+ years building distributed systems and backend services at scale
- Ads domain experience (2+ years): worked on ad serving, delivery, or marketplace systems
- Experience with ML model serving infrastructure: real-time inference, model deployment pipelines, feature hydration, fallback strategies
- Built or worked on core ad tech systems: ad servers, bidders, pacers, or ranking and scoring components
- Built APIs and backend services that integrate across a multi-team platform
- Understanding of ad serving concepts: inventory management, frequency capping, member ad experience quality, and supply-demand dynamics
- Comfortable working at the intersection of engineering and data science, productionizing ML models into low-latency serving paths
- Ability to operate in an environment that is a mix of big-tech scale and startup speed
Nice to Haves
- Experience with auction mechanics: first-price, second-price, reserve pricing, bid shading
- Experience building multi-stage ranking systems (retrieval, scoring, reranking), podding and ad break planning
- Built or improved budget pacing and delivery control systems
- Familiar with CTV constraints: server-side ad insertion, live event ad serving at scale
- Experience with experimentation infrastructure: A/B testing, holdout groups, marketplace experiments
- Built simulation or counterfactual testing platforms for marketplace or auction systems
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 $388,000.00 - $619,000.00.
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.
Netflix is a unique culture and environment.
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 Visa Sponsorship as a Distributed Systems Engineer
Target infrastructure-heavy engineering teams
Companies running large-scale distributed systems, think cloud platforms, fintech, and streaming services, sponsor the most consistently. These teams have ongoing headcount needs and established immigration pipelines, making sponsorship a standard part of hiring.
Lead with systems design depth in your resume
USCIS approves H-1B petitions for distributed systems roles based on specialty occupation criteria. Resumes that demonstrate theoretical depth, such as consensus algorithms, fault tolerance, or distributed transactions, strengthen the case that a bachelor's degree in CS is required.
Factor cap-exempt employers into your search
Universities, nonprofit research labs, and certain government-affiliated organizations are exempt from the H-1B lottery. Distributed systems roles exist at these institutions, and cap-exempt sponsorship means you can start immediately without waiting for the annual lottery cycle.
Understand that O-1A is a real alternative
If you've published research, spoken at systems conferences like OSDI or SOSP, or led widely adopted open-source infrastructure projects, you may qualify for an O-1A. This visa bypasses the lottery entirely and is increasingly viable for senior engineers.
Check LCA filings to verify sponsorship history
Employers file Labor Condition Applications publicly for every H-1B hire. Searching the Department of Labor's OFLC disclosure database by company name shows whether a prospective employer has actually sponsored engineers recently, not just claimed they do.
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Find Distributed Systems Engineer JobsFrequently Asked Questions
Is distributed systems engineer a specialty occupation for H-1B purposes?
Yes. Distributed systems engineering consistently qualifies as a specialty occupation under H-1B rules because the role normally requires at least a bachelor's degree in computer science, computer engineering, or a closely related field. USCIS has approved thousands of H-1B petitions for this job title. Roles focused on consensus protocols, distributed storage, or large-scale reliability are particularly well-supported by the specialty occupation standard.
Do I need a computer science degree specifically, or will a related field work?
A degree in computer science, electrical engineering, mathematics, or software engineering all support an H-1B petition for this role. The key is that your degree field connects logically to distributed systems work. If your degree is in an unrelated field, three years of directly relevant professional experience can substitute for each year of missing education under USCIS equivalency rules.
Which types of employers sponsor distributed systems engineers most reliably?
Cloud infrastructure companies, large-scale fintech firms, streaming platforms, and database companies sponsor the most distributed systems engineers. These organizations run complex internal systems that require specialized expertise and have legal teams experienced with H-1B petitions. You can browse verified sponsoring employers on Migrate Mate, where all listed roles include visa sponsorship.
How does the H-1B lottery affect my chances if I have a master's degree in CS?
A U.S. master's degree in a qualifying STEM field enters you into the advanced degree exemption pool, which is drawn first. In recent fiscal years, the master's cap selection rate has been meaningfully higher than the regular cap rate. If you earned your master's outside the U.S., you compete in the general pool only, though the practical difference in selection odds has narrowed as overall registrations have grown.
Can I switch employers mid-H-1B if I find a better distributed systems role?
Yes. Under H-1B portability rules, you can start working for a new employer as soon as they file an H-1B transfer petition, without waiting for approval, provided your current H-1B was properly approved and you've maintained valid status. Your new employer files a fresh Form I-129 with an updated Labor Condition Application reflecting the new role and location.
What is the prevailing wage requirement for sponsored Distributed Systems Engineer jobs?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.
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