E-3 Visa Applied Scientist Jobs
Applied Scientist roles qualify as E-3 specialty occupations when the position requires a degree in computer science, statistics, machine learning, or a related quantitative field. Australian nationals can secure E-3 visa sponsorship without entering a lottery, with renewals available indefinitely as long as you hold a qualifying offer.
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Get Access To All JobsABOUT CRUNCHYROLL
Founded by fans, Crunchyroll delivers the art and culture of anime to a passionate community. We super-serve over 100 million anime and manga fans across 200+ countries and territories, and help them connect with the stories and characters they crave. Whether that experience is online or in-person, streaming video, theatrical, games, merchandise, events and more, it’s powered by the anime content we all love.
Join our team, and help us shape the future of anime!
We are hiring an Applied Scientist to help advance personalization across the Crunchyroll ecosystem. In this role, you will lead the scientific development of recommendation, ranking, and decisioning solutions that improve how fans discover and engage with anime series/movies, manga, merchandise, games, and other areas in the anime fandom. You will partner closely with Machine Learning Engineers, Product, Engineering, Marketing, and Content stakeholders to make Crunchyroll the ultimate destination for anime experience.
ABOUT THE ROLE
In the role of Senior Applied Scientist for Recommendation and Personalization, you will report to the Director of Data Science and Machine Learning in our Center for Data and Insights. You will own the research and applied science agenda for personalization, from problem framing and data exploration through model development, evaluation, experimentation, and iteration. This role is ideal for someone who enjoys combining strong scientific rigor with product thinking to improve user discovery, engagement, retention, and long-term fan value.
You will work across multiple user touchpoints, including app and web interfaces, lifecycle and promotional email campaigns, and flywheels that connect video, ecommerce, manga, and adjacent experiences. You will help define what great personalization looks like at Crunchyroll, build the evidence to prove impact, and collaborate with engineering partners to ensure the resulting solutions can be productionized effectively.
Core areas of responsibility
- Lead the research and development of recommendation, ranking, retrieval, and personalization methods tailored to Crunchyroll use cases across streaming, manga, ecommerce, and lifecycle marketing surfaces.
- Frame ambiguous business and product questions into clear scientific problems, hypotheses, success metrics, and experimentation plans.
- Design and run robust offline evaluation frameworks for recommender systems, including relevance, diversity, novelty, coverage, calibration, and long-term value metrics.
- Partner with Product, Analytics, and Engineering to define online experiments, interpret results, and turn learnings into roadmap decisions and model improvements.
- Develop user, content, and contextual understanding through feature design, representation learning, segmentation, and behavioral analysis.
- Prototype and evaluate a range of approaches, including collaborative filtering, content-based methods, sequence modeling, deep learning, bandits, causal or uplift methods, and LLM-enabled recommendation techniques where appropriate.
- Analyze user feedback loops and cross-domain interactions to improve discovery across video, merchandise, manga, and other ecosystem experiences.
- Work closely with Machine Learning Engineers to translate promising research into production-ready solutions on our in-house recommendation platform.
- Communicate scientific findings, model tradeoffs, and business implications clearly to technical and non-technical stakeholders.
- Help establish best practices for experimentation, reproducibility, model governance, and scientific documentation within the personalization and recommendations function.
ABOUT YOU
We get excited about candidates, like you, because you have:
Experience: You bring 5+ years of experience in applied machine learning, recommendation systems, search/ranking, experimentation, or a closely related area, with a track record of driving measurable product impact.
Scientific Depth: You have strong foundations in machine learning, statistics, experimental design, and causal thinking, and you know how to choose the right level of modeling complexity for the problem at hand.
Recommendation Expertise: You have hands-on experience with at least some of the following: collaborative filtering, retrieval and ranking systems, representation learning, sequence / generative models, bandits, graph methods, or personalization for consumer products.
Technical Skills: You are highly proficient in Python and comfortable working with common ML libraries such as PyTorch, TensorFlow, Scikit-learn, XGBoost, or similar tooling. Experience working with SQL, distributed data processing, and cloud-based ML workflows is strongly preferred.
Experimentation Mindset: You know how to design offline and online evaluations, reason carefully about metrics, and connect experimental findings to user and business outcomes.
Cross-Functional Collaboration: You have experience partnering effectively with engineers, product managers, analysts, marketers, and business stakeholders to move from idea to execution.
Communication Skills: You can explain sophisticated modeling decisions and ambiguous findings in a clear, decision-oriented way to diverse audiences.
Educational Background: You hold an MS or PhD in Computer Science, Machine Learning, Statistics, Operations Research, Economics, or a related quantitative discipline, or you bring equivalent applied industry experience.
NICE TO HAVE
- Experience personalizing content, commerce, media, entertainment, gaming, or subscription products at scale.
- Familiarity with recommender-system failure modes such as popularity bias, cold start, sparse feedback, and feedback loop effects.
- Experience with multi-objective optimization, constrained ranking, or balancing short-term engagement with long-term user value.
- Exposure to generative AI, representation learning, or LLM applications that support recommendation and personalization workflows.
- Published research, patents, or open-source contributions in recommendation systems, personalization, applied machine learning, or experimentation.
ABOUT THE TEAM
Our centralized DS/ML team serves stakeholders across Finance, Product, Engineering, Marketing, Creatives, and Content Operations with data-driven and ML/AI-powered solutions. Within that broader organization, the Personalization and Recommendation group is building the next generation capabilities to power tailored fan experiences across every major user interface and lifecycle touchpoint. Today, the team includes engineers focused on operationalizing our recommendation platform with strong engineering excellence. This Applied Scientist role complements that foundation by bringing deeper scientific ownership to modeling strategy, evaluation, and experimentation, while partnering closely with an additional MLE hire to accelerate production impact.
WHY THIS ROLE IS EXCITING
- You will help define personalization strategy across multiple surfaces instead of optimizing a single narrow funnel.
- You will work on problems that span content discovery, user engagement, retention, and cross-domain ecosystem value.
- You will influence both what we build and how we measure success, with strong exposure to partners across the business.
- You will join at a formative moment, with the opportunity to shape team standards, technical direction, and long-term roadmap.
WHY YOU WILL LOVE WORKING AT CRUNCHYROLL
In addition to getting to work with fun, passionate and inspired colleagues, you will also enjoy the following benefits and perks:
- Receive a great compensation package including salary plus performance bonus earning potential, paid annually.
- Flexible time off policies allowing you to take the time you need to be your whole self.
- Generous medical, dental, vision, STD, LTD, and life insurance
- Health Saving Account HSA program
- Health care and dependent care FSA
- 401(k) plan, with employer match
- Employer paid commuter benefit
- Support program for new parents
- Pet insurance and some of our offices are pet friendly!
COMPENSATION
- Pay Transparency - Los Angeles, CA: $185,000—$230,000 USD
- Pay Transparency - San Francisco, CA: $205,000—$245,000 USD
The Pay Range for this position is listed. Actual pay will vary based on factors including, but not limited to location, experience, and performance. The range listed is just one component of Crunchyroll’s Total Rewards offerings for employees. Other rewards may include performance bonuses, employer matched retirement savings, time-off programs, and progressive health benefits and perks.
ABOUT OUR VALUES
We want to be everything for someone rather than something for everyone and we do this by living and modeling our values in all that we do. We value:
- Courage. We believe that when we overcome fear, we enable our best selves.
- Curiosity. We are curious, which is the gateway to empathy, inclusion, and understanding.
- Kaizen. We have a growth mindset committed to constant forward progress.
- Service. We serve our community with humility, enabling joy and belonging for others.
OUR COMMITMENT TO DIVERSITY AND INCLUSION
Our mission of helping people belong reflects our commitment to diversity & inclusion. It's just the way we do business.
We are an equal opportunity employer and value diversity at Crunchyroll. Pursuant to applicable law, we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Crunchyroll, LLC is an independently operated joint venture between US-based Sony Pictures Entertainment, and Japan's Aniplex, a subsidiary of Sony Music Entertainment (Japan) Inc., both subsidiaries of Tokyo-based Sony Group Corporation.
Questions about Crunchyroll’s hiring process? Please check out our Hiring FAQs:
Please refer to our Candidate Privacy Policy for more information about how we process your personal information, and your data protection rights.
Please beware of recent scams to online job seekers. Those applying to our job openings will only be contacted directly from @crunchyroll.com email account.
ABOUT CRUNCHYROLL
Founded by fans, Crunchyroll delivers the art and culture of anime to a passionate community. We super-serve over 100 million anime and manga fans across 200+ countries and territories, and help them connect with the stories and characters they crave. Whether that experience is online or in-person, streaming video, theatrical, games, merchandise, events and more, it’s powered by the anime content we all love.
Join our team, and help us shape the future of anime!
We are hiring an Applied Scientist to help advance personalization across the Crunchyroll ecosystem. In this role, you will lead the scientific development of recommendation, ranking, and decisioning solutions that improve how fans discover and engage with anime series/movies, manga, merchandise, games, and other areas in the anime fandom. You will partner closely with Machine Learning Engineers, Product, Engineering, Marketing, and Content stakeholders to make Crunchyroll the ultimate destination for anime experience.
ABOUT THE ROLE
In the role of Senior Applied Scientist for Recommendation and Personalization, you will report to the Director of Data Science and Machine Learning in our Center for Data and Insights. You will own the research and applied science agenda for personalization, from problem framing and data exploration through model development, evaluation, experimentation, and iteration. This role is ideal for someone who enjoys combining strong scientific rigor with product thinking to improve user discovery, engagement, retention, and long-term fan value.
You will work across multiple user touchpoints, including app and web interfaces, lifecycle and promotional email campaigns, and flywheels that connect video, ecommerce, manga, and adjacent experiences. You will help define what great personalization looks like at Crunchyroll, build the evidence to prove impact, and collaborate with engineering partners to ensure the resulting solutions can be productionized effectively.
Core areas of responsibility
- Lead the research and development of recommendation, ranking, retrieval, and personalization methods tailored to Crunchyroll use cases across streaming, manga, ecommerce, and lifecycle marketing surfaces.
- Frame ambiguous business and product questions into clear scientific problems, hypotheses, success metrics, and experimentation plans.
- Design and run robust offline evaluation frameworks for recommender systems, including relevance, diversity, novelty, coverage, calibration, and long-term value metrics.
- Partner with Product, Analytics, and Engineering to define online experiments, interpret results, and turn learnings into roadmap decisions and model improvements.
- Develop user, content, and contextual understanding through feature design, representation learning, segmentation, and behavioral analysis.
- Prototype and evaluate a range of approaches, including collaborative filtering, content-based methods, sequence modeling, deep learning, bandits, causal or uplift methods, and LLM-enabled recommendation techniques where appropriate.
- Analyze user feedback loops and cross-domain interactions to improve discovery across video, merchandise, manga, and other ecosystem experiences.
- Work closely with Machine Learning Engineers to translate promising research into production-ready solutions on our in-house recommendation platform.
- Communicate scientific findings, model tradeoffs, and business implications clearly to technical and non-technical stakeholders.
- Help establish best practices for experimentation, reproducibility, model governance, and scientific documentation within the personalization and recommendations function.
ABOUT YOU
We get excited about candidates, like you, because you have:
Experience: You bring 5+ years of experience in applied machine learning, recommendation systems, search/ranking, experimentation, or a closely related area, with a track record of driving measurable product impact.
Scientific Depth: You have strong foundations in machine learning, statistics, experimental design, and causal thinking, and you know how to choose the right level of modeling complexity for the problem at hand.
Recommendation Expertise: You have hands-on experience with at least some of the following: collaborative filtering, retrieval and ranking systems, representation learning, sequence / generative models, bandits, graph methods, or personalization for consumer products.
Technical Skills: You are highly proficient in Python and comfortable working with common ML libraries such as PyTorch, TensorFlow, Scikit-learn, XGBoost, or similar tooling. Experience working with SQL, distributed data processing, and cloud-based ML workflows is strongly preferred.
Experimentation Mindset: You know how to design offline and online evaluations, reason carefully about metrics, and connect experimental findings to user and business outcomes.
Cross-Functional Collaboration: You have experience partnering effectively with engineers, product managers, analysts, marketers, and business stakeholders to move from idea to execution.
Communication Skills: You can explain sophisticated modeling decisions and ambiguous findings in a clear, decision-oriented way to diverse audiences.
Educational Background: You hold an MS or PhD in Computer Science, Machine Learning, Statistics, Operations Research, Economics, or a related quantitative discipline, or you bring equivalent applied industry experience.
NICE TO HAVE
- Experience personalizing content, commerce, media, entertainment, gaming, or subscription products at scale.
- Familiarity with recommender-system failure modes such as popularity bias, cold start, sparse feedback, and feedback loop effects.
- Experience with multi-objective optimization, constrained ranking, or balancing short-term engagement with long-term user value.
- Exposure to generative AI, representation learning, or LLM applications that support recommendation and personalization workflows.
- Published research, patents, or open-source contributions in recommendation systems, personalization, applied machine learning, or experimentation.
ABOUT THE TEAM
Our centralized DS/ML team serves stakeholders across Finance, Product, Engineering, Marketing, Creatives, and Content Operations with data-driven and ML/AI-powered solutions. Within that broader organization, the Personalization and Recommendation group is building the next generation capabilities to power tailored fan experiences across every major user interface and lifecycle touchpoint. Today, the team includes engineers focused on operationalizing our recommendation platform with strong engineering excellence. This Applied Scientist role complements that foundation by bringing deeper scientific ownership to modeling strategy, evaluation, and experimentation, while partnering closely with an additional MLE hire to accelerate production impact.
WHY THIS ROLE IS EXCITING
- You will help define personalization strategy across multiple surfaces instead of optimizing a single narrow funnel.
- You will work on problems that span content discovery, user engagement, retention, and cross-domain ecosystem value.
- You will influence both what we build and how we measure success, with strong exposure to partners across the business.
- You will join at a formative moment, with the opportunity to shape team standards, technical direction, and long-term roadmap.
WHY YOU WILL LOVE WORKING AT CRUNCHYROLL
In addition to getting to work with fun, passionate and inspired colleagues, you will also enjoy the following benefits and perks:
- Receive a great compensation package including salary plus performance bonus earning potential, paid annually.
- Flexible time off policies allowing you to take the time you need to be your whole self.
- Generous medical, dental, vision, STD, LTD, and life insurance
- Health Saving Account HSA program
- Health care and dependent care FSA
- 401(k) plan, with employer match
- Employer paid commuter benefit
- Support program for new parents
- Pet insurance and some of our offices are pet friendly!
COMPENSATION
- Pay Transparency - Los Angeles, CA: $185,000—$230,000 USD
- Pay Transparency - San Francisco, CA: $205,000—$245,000 USD
The Pay Range for this position is listed. Actual pay will vary based on factors including, but not limited to location, experience, and performance. The range listed is just one component of Crunchyroll’s Total Rewards offerings for employees. Other rewards may include performance bonuses, employer matched retirement savings, time-off programs, and progressive health benefits and perks.
ABOUT OUR VALUES
We want to be everything for someone rather than something for everyone and we do this by living and modeling our values in all that we do. We value:
- Courage. We believe that when we overcome fear, we enable our best selves.
- Curiosity. We are curious, which is the gateway to empathy, inclusion, and understanding.
- Kaizen. We have a growth mindset committed to constant forward progress.
- Service. We serve our community with humility, enabling joy and belonging for others.
OUR COMMITMENT TO DIVERSITY AND INCLUSION
Our mission of helping people belong reflects our commitment to diversity & inclusion. It's just the way we do business.
We are an equal opportunity employer and value diversity at Crunchyroll. Pursuant to applicable law, we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Crunchyroll, LLC is an independently operated joint venture between US-based Sony Pictures Entertainment, and Japan's Aniplex, a subsidiary of Sony Music Entertainment (Japan) Inc., both subsidiaries of Tokyo-based Sony Group Corporation.
Questions about Crunchyroll’s hiring process? Please check out our Hiring FAQs:
Please refer to our Candidate Privacy Policy for more information about how we process your personal information, and your data protection rights.
Please beware of recent scams to online job seekers. Those applying to our job openings will only be contacted directly from @crunchyroll.com email account.
See all 204+ Applied Scientist jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Applied Scientist roles.
Get Access To All JobsTips for Finding E-3 Visa Sponsorship as an Applied Scientist
Translate your Australian credentials for U.S. employers
A three-year Australian bachelor's degree is generally accepted as equivalent to a U.S. four-year degree for E-3 purposes. Get a credential evaluation from a NACES-approved evaluator before your first interview so you're ready when employers ask.
Target employers with active DOL filing histories
Search the DOL's Office of Foreign Labor Certification disclosure data to identify companies that have filed Labor Condition Applications for Applied Scientist or Machine Learning Engineer roles. These employers already understand the E-3 process and won't need educating.
Find E-3 sponsoring employers on Migrate Mate
Use Migrate Mate's E-3 filing service to surface companies actively sponsoring Applied Scientist roles and handle your LCA and visa paperwork end-to-end, from offer letter to consulate appointment.
Clarify the specialty occupation case early
Applied Scientist roles are strong E-3 candidates, but job descriptions that list a degree as 'preferred' rather than 'required' can create issues at the consulate. Ask your employer to confirm the job description specifies a degree as a minimum requirement before the LCA is filed.
Understand your employer's LCA timeline before accepting
Your employer files the LCA with DOL before you can apply for the E-3 visa. Standard DOL certification takes around seven business days. Confirm your employer knows this step exists and has HR capacity to move quickly after you accept an offer.
Applied Scientist jobs are hiring across the US. Find yours.
Find Applied Scientist JobsApplied Scientist E-3 Visa: Frequently Asked Questions
How do I find Applied Scientist jobs with E-3 visa sponsorship?
Migrate Mate is the most direct way to search for Applied Scientist roles where employers are already set up to sponsor E-3 visas. Many roles in machine learning, data science infrastructure, and research engineering qualify as specialty occupations under the E-3, but finding employers who understand the filing process is the real challenge. Migrate Mate filters for that specifically.
How much does it cost to get an E-3 visa?
Migrate Mate's E-3 filing service covers the entire process for $499, including the Labor Condition Application, visa document preparation, and consulate appointment guidance. Traditional immigration lawyers charge $2,000–$5,000+ for the same work. The E-3 has less paperwork than most work visas, so paying thousands for legal help is usually unnecessary.
Is the E-3 visa better than H-1B for Applied Scientist roles?
For Australian nationals, the E-3 is almost always the better path. There is no lottery, no annual cap pressure, and the application goes directly to a U.S. consulate in Australia rather than through USCIS. Applied Scientist roles qualify as specialty occupations under both visa types, but the E-3 lets you start the process after receiving an offer without waiting for a registration window in April.
Does my Applied Scientist role qualify as a specialty occupation for the E-3?
Applied Scientist roles that require a bachelor's degree or higher in computer science, statistics, applied mathematics, or a related quantitative field consistently qualify as specialty occupations. The key is that the degree requirement must be specific to the field, not general. Roles where any bachelor's degree is acceptable regardless of major are harder to support, so the job description wording matters.
Can I switch Applied Scientist employers while on an E-3 visa?
Yes, but each new employer must file a fresh LCA with DOL and you'll need a new E-3 visa stamp before re-entering the U.S. if you travel internationally. If you stay in the U.S. and don't travel, you can begin working for the new employer once the new LCA is certified and you have a valid offer, though the visa stamp from the prior employer will need to be updated at your next consular visit.
See which Applied Scientist employers are hiring and sponsoring visas right now.
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