H-1B Visa Distributed Systems Engineer Jobs
Distributed Systems Engineer roles sit squarely within H-1B specialty occupation criteria, requiring at least a bachelor's degree in computer science, software engineering, or a directly related field. Large tech employers, cloud infrastructure companies, and fintech firms file LCAs for this role regularly, making it one of the more sponsor-accessible titles in the H-1B market.
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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 H-1B Visa Sponsorship as a Distributed Systems Engineer
Align your degree to the role
USCIS evaluates whether your specific degree field directly supports the job duties. A computer science or software engineering degree maps cleanly, but an unrelated STEM degree may require a credential evaluation letter explaining the connection to distributed systems work.
Filter employers by LCA filing history
Use Migrate Mate to search verified DOL Labor Condition Application filings for Distributed Systems Engineer roles. This shows you which companies have already completed the employer-side compliance step, not just which ones claim to sponsor.
Benchmark your wage against the prevailing rate
Run your target job title and metro area through the OFLC Wage Search before negotiating. Your offered salary must meet the DOL prevailing wage for the role's SOC code, and distributed systems positions often map to higher wage levels in major tech markets.
Get your credentials evaluated before interviewing
If your degree is from outside the U.S., a NACES-member credential evaluation documenting U.S. equivalency speeds up the LCA and I-129 stages. Employers filing H-1B petitions need this before USCIS can confirm specialty occupation eligibility.
Clarify petition timing during the offer stage
H-1B cap filings open in March for an October 1 start. If you're interviewing in summer or fall, ask whether the employer will file in the next registration window or hold the role. Cap-exempt employers at universities or nonprofit research labs can file any time.
Distributed Systems Engineer jobs are hiring across the US. Find yours.
Find Distributed Systems Engineer JobsDistributed Systems Engineer H-1B Visa: Frequently Asked Questions
Does a Distributed Systems Engineer role qualify for H-1B sponsorship?
Yes. Distributed systems engineering meets the H-1B specialty occupation definition because the role typically requires at least a bachelor's degree in computer science, software engineering, or a closely related field. The O*NET profile for software developers and systems engineers supports this classification. Employers confirm the requirement through the LCA filing, which documents the job duties and minimum degree requirement.
Which types of employers sponsor H-1B visas for this role?
Cloud infrastructure companies, large-scale tech platforms, financial technology firms, and enterprise software companies are frequent sponsors for distributed systems roles. Cap-exempt employers, including research universities and affiliated nonprofits, can file H-1B petitions outside the annual lottery window. Browse Migrate Mate to see which companies have active LCA filings for this specific job title.
How does the H-1B lottery affect my job search as a distributed systems engineer?
Cap-subject H-1B petitions are subject to an annual lottery with registration in March and an October 1 start date. If you're on OPT when you're selected, cap-gap rules extend your work authorization through September 30. Cap-exempt employers at qualifying research institutions and nonprofits aren't subject to the lottery, so targeting those organizations can eliminate timing uncertainty.
What does the LCA process mean for distributed systems roles specifically?
Your employer files a Labor Condition Application with the DOL before submitting your H-1B petition to USCIS. For distributed systems engineers, the LCA certifies that your offered wage meets or exceeds the prevailing wage for the role's SOC code in your work location. Roles in high-cost metros like San Francisco or Seattle typically fall under higher DOL wage levels, which the employer must commit to in writing.
Can I switch employers after my H-1B is approved for a distributed systems role?
Yes, H-1B portability under AC21 lets you change employers while a new I-129 petition is pending, as long as you've had H-1B status for at least 180 days and the new role is in the same or a similar occupational classification. Distributed systems roles generally port well across tech employers because the SOC code and specialty occupation basis remain consistent. USCIS reviews the new petition independently.
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