Machine Learning Scientist Jobs for OPT Students
Machine Learning Scientist roles are among the most actively sponsored positions for F-1 OPT students, with STEM OPT extensions available for up to three years. Most employers require a master's or PhD in computer science, statistics, or a related field, and STEM designation makes these roles strong candidates for H-1B sponsorship.
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Get Access To All JobsINTRODUCTION
Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success.
Why Join Us?
To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win.
We provide a full benefits package, including exciting travel perks, generous time-off, parental leave, a flexible work model (with some pretty cool offices), and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey. We’re building a more open world. Join us.
Introduction to team:
Are you passionate about using machine learning to improve Customer Experience? Would you like to work in the fast-paced, competitive, customer-focused, and data-rich world of online travel?
Our Machine Learning and Data Science team are growing! We are looking to hire researchers and data scientists interested in breaking new ground to tackle some of the most complex customer experience problems in the travel domain. The focus of your job will be on developing state-of-the-art machine learning algorithms to power and enhance the customer experience across highly complex post-booking recommendations, customer service, and trip management use cases. You will tackle substantial technical challenges, from inference problems arising from long-tail traveler data to multi-objective optimization problems in the highly dynamic, operationally complex environment of customer service. Your passion for the craft of ML and AI will unlock tangible growth for our business by exploiting these rich data sets and building effective solutions for travelers and our partners.
This is your opportunity to build the core algorithms that help Expedia Group's Post Booking organization bring context and intelligence to every step of the traveler journey and redefine what service excellence in travel can be. We are looking for a hands-on scientist who is passionate about applying machine learning to complex prediction and optimization problems that drive an ecosystem that anticipates traveler needs, personalizes dynamic add-ons and upsells, and improves service experiences, making travel more seamless for millions of customers and partners worldwide.
What You'll Do:
- Design & Implement ML Solutions: Take ownership of the end-to-end ML lifecycle for your projects, from ideation and research to deployment and monitoring.
- Test, Learn, and Iterate: Design and analyze tests to validate your models and quantify their business impact and design future iterations.
- Collaborate and Communicate: Partner closely with product managers, engineers, and business stakeholders to understand requirements, define problems, and communicate your findings and results effectively.
Who you are:
Experience & Education
- PhD or MS in a quantitative field (e.g., Computer Science, Economics, Statistics, Physics).
- 3+ years of hands-on industry experience building and deploying machine learning models to solve real-world problems.
Functional & Technical Skills
- Expertise in applied ML: Deep, practical knowledge of machine learning theory (supervised/unsupervised learning, deep learning) and statistical modeling and a strong command of experimental design (A/B testing) and causal inference to accurately measure impact. Able to design end-to-end ML solutions: framing the problem, choosing data sources, selecting algorithms, and defining evaluation strategy. Experience with the machine learning software development lifecycle, including experimentation, deployment, monitoring, and iteration in production. Strong programming skills in at least one major ML language (e.g., Python, Scala, Java) plus SQL; writes clean, modular, maintainable code.
- Technical Fluency: Strong programming skills in Python and its data science ecosystem (e.g., pandas, scikit-learn, pySpark), plus proficiency in SQL. Follow software engineering best practices and contribute to the team's shared codebase.
- First-Principles Problem Solver: Skilled at dissecting ambiguous problems and clearly communicating complex technical ideas.
Highly Desired Experience
- Domain knowledge in customer service, recommendation systems, operational applications of ML, and/or e-commerce
- Experience with reinforcement learning or other advanced ML techniques is a plus
- Experience building and deploying models using GenAI/LLM technologies
- Experience translating research and academic papers into improved model designs and techniques
Minimum Qualifications:
- Bachelor’s degree in Computer Science or a related technical field; or Equivalent related professional experience.
- 5+ years of relevant professional experience.
- Proven ability to design end-to-end ML solutions, including problem formulation, identification and preparation of data sources, algorithm selection, feature engineering, evaluation strategy, and production deployment and monitoring.
- Strong programming skills in Python and its data science ecosystem (such as pandas, scikit-learn, PySpark) and proficiency in SQL, with experience following software engineering best practices and contributing to shared codebases.
- Familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products, including experience with the machine learning software development lifecycle from experimentation through operational monitoring.
Preferred Qualifications:
- MS or PhD in a quantitative field such as Computer Science, Economics, Statistics, Physics, or a related discipline.
- 3+ years of hands-on industry experience building, deploying, and iterating on machine learning models that solve real-world problems in production environments.
- Proven ability to design end-to-end ML solutions, including problem formulation, identification and preparation of data sources, algorithm selection, feature engineering, evaluation strategy, and production deployment and monitoring.
- Strong programming skills in Python and its data science ecosystem (such as pandas, scikit-learn, PySpark) and proficiency in SQL, with experience following software engineering best practices and contributing to shared codebases.
- Familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products, including experience with the machine learning software development lifecycle from experimentation through operational monitoring.
Expedia Group is proud to offer a wide range of benefits to support employees and their families, including medical/dental/vision, paid time off, and an Employee Assistance Program. To fuel each employee’s passion for travel, we offer a wellness & travel reimbursement, travel discounts, and an International Airlines Travel Agent (IATAN) membership. View our full list of benefits.
The total cash range for this position in Seattle is $137,500.00 to $192,500.00. Employees in this role have the potential to increase their pay up to $220,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role. The total cash range for this position in San Jose is $149,000.00 to $208,500.00. Employees in this role have the potential to increase their pay up to $238,500.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role. Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience. Pay ranges may be modified in the future.
Accommodation requests
If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request.
We are proud to be named as a Best Place to Work on Glassdoor in 2024 and be recognized for award-winning culture by organizations like Forbes, TIME, Disability:IN, and others.
Expedia Group's family of brands includes: Brand Expedia®, Hotels.com®, Expedia® Partner Solutions, Vrbo®, trivago®, Orbitz®, Travelocity®, Hotwire®, Wotif®, ebookers®, CheapTickets®, Expedia Group™ Media Solutions, Expedia Local Expert®, CarRentals.com™, and Expedia Cruises™. © 2024 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. CST: 2029030-50
Employment opportunities and job offers at Expedia Group will always come from Expedia Group’s Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you’re confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official website to find and apply for job openings at Expedia Group is careers.expediagroup.com/jobs.
Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.
INTRODUCTION
Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success.
Why Join Us?
To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win.
We provide a full benefits package, including exciting travel perks, generous time-off, parental leave, a flexible work model (with some pretty cool offices), and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey. We’re building a more open world. Join us.
Introduction to team:
Are you passionate about using machine learning to improve Customer Experience? Would you like to work in the fast-paced, competitive, customer-focused, and data-rich world of online travel?
Our Machine Learning and Data Science team are growing! We are looking to hire researchers and data scientists interested in breaking new ground to tackle some of the most complex customer experience problems in the travel domain. The focus of your job will be on developing state-of-the-art machine learning algorithms to power and enhance the customer experience across highly complex post-booking recommendations, customer service, and trip management use cases. You will tackle substantial technical challenges, from inference problems arising from long-tail traveler data to multi-objective optimization problems in the highly dynamic, operationally complex environment of customer service. Your passion for the craft of ML and AI will unlock tangible growth for our business by exploiting these rich data sets and building effective solutions for travelers and our partners.
This is your opportunity to build the core algorithms that help Expedia Group's Post Booking organization bring context and intelligence to every step of the traveler journey and redefine what service excellence in travel can be. We are looking for a hands-on scientist who is passionate about applying machine learning to complex prediction and optimization problems that drive an ecosystem that anticipates traveler needs, personalizes dynamic add-ons and upsells, and improves service experiences, making travel more seamless for millions of customers and partners worldwide.
What You'll Do:
- Design & Implement ML Solutions: Take ownership of the end-to-end ML lifecycle for your projects, from ideation and research to deployment and monitoring.
- Test, Learn, and Iterate: Design and analyze tests to validate your models and quantify their business impact and design future iterations.
- Collaborate and Communicate: Partner closely with product managers, engineers, and business stakeholders to understand requirements, define problems, and communicate your findings and results effectively.
Who you are:
Experience & Education
- PhD or MS in a quantitative field (e.g., Computer Science, Economics, Statistics, Physics).
- 3+ years of hands-on industry experience building and deploying machine learning models to solve real-world problems.
Functional & Technical Skills
- Expertise in applied ML: Deep, practical knowledge of machine learning theory (supervised/unsupervised learning, deep learning) and statistical modeling and a strong command of experimental design (A/B testing) and causal inference to accurately measure impact. Able to design end-to-end ML solutions: framing the problem, choosing data sources, selecting algorithms, and defining evaluation strategy. Experience with the machine learning software development lifecycle, including experimentation, deployment, monitoring, and iteration in production. Strong programming skills in at least one major ML language (e.g., Python, Scala, Java) plus SQL; writes clean, modular, maintainable code.
- Technical Fluency: Strong programming skills in Python and its data science ecosystem (e.g., pandas, scikit-learn, pySpark), plus proficiency in SQL. Follow software engineering best practices and contribute to the team's shared codebase.
- First-Principles Problem Solver: Skilled at dissecting ambiguous problems and clearly communicating complex technical ideas.
Highly Desired Experience
- Domain knowledge in customer service, recommendation systems, operational applications of ML, and/or e-commerce
- Experience with reinforcement learning or other advanced ML techniques is a plus
- Experience building and deploying models using GenAI/LLM technologies
- Experience translating research and academic papers into improved model designs and techniques
Minimum Qualifications:
- Bachelor’s degree in Computer Science or a related technical field; or Equivalent related professional experience.
- 5+ years of relevant professional experience.
- Proven ability to design end-to-end ML solutions, including problem formulation, identification and preparation of data sources, algorithm selection, feature engineering, evaluation strategy, and production deployment and monitoring.
- Strong programming skills in Python and its data science ecosystem (such as pandas, scikit-learn, PySpark) and proficiency in SQL, with experience following software engineering best practices and contributing to shared codebases.
- Familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products, including experience with the machine learning software development lifecycle from experimentation through operational monitoring.
Preferred Qualifications:
- MS or PhD in a quantitative field such as Computer Science, Economics, Statistics, Physics, or a related discipline.
- 3+ years of hands-on industry experience building, deploying, and iterating on machine learning models that solve real-world problems in production environments.
- Proven ability to design end-to-end ML solutions, including problem formulation, identification and preparation of data sources, algorithm selection, feature engineering, evaluation strategy, and production deployment and monitoring.
- Strong programming skills in Python and its data science ecosystem (such as pandas, scikit-learn, PySpark) and proficiency in SQL, with experience following software engineering best practices and contributing to shared codebases.
- Familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products, including experience with the machine learning software development lifecycle from experimentation through operational monitoring.
Expedia Group is proud to offer a wide range of benefits to support employees and their families, including medical/dental/vision, paid time off, and an Employee Assistance Program. To fuel each employee’s passion for travel, we offer a wellness & travel reimbursement, travel discounts, and an International Airlines Travel Agent (IATAN) membership. View our full list of benefits.
The total cash range for this position in Seattle is $137,500.00 to $192,500.00. Employees in this role have the potential to increase their pay up to $220,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role. The total cash range for this position in San Jose is $149,000.00 to $208,500.00. Employees in this role have the potential to increase their pay up to $238,500.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role. Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience. Pay ranges may be modified in the future.
Accommodation requests
If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request.
We are proud to be named as a Best Place to Work on Glassdoor in 2024 and be recognized for award-winning culture by organizations like Forbes, TIME, Disability:IN, and others.
Expedia Group's family of brands includes: Brand Expedia®, Hotels.com®, Expedia® Partner Solutions, Vrbo®, trivago®, Orbitz®, Travelocity®, Hotwire®, Wotif®, ebookers®, CheapTickets®, Expedia Group™ Media Solutions, Expedia Local Expert®, CarRentals.com™, and Expedia Cruises™. © 2024 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. CST: 2029030-50
Employment opportunities and job offers at Expedia Group will always come from Expedia Group’s Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you’re confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official website to find and apply for job openings at Expedia Group is careers.expediagroup.com/jobs.
Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.
How to Get Visa Sponsorship as a Machine Learning Scientist
Target research-driven employers
Companies with dedicated AI research divisions, such as large tech firms and well-funded startups, file H-1B petitions at far higher rates than generalist employers. Search Migrate Mate to find Machine Learning Scientist roles at employers with verified sponsorship history.
Lead with published research and benchmarks
Hiring managers for Machine Learning Scientist roles respond to concrete outcomes: papers published, benchmark improvements, and model performance gains. Quantified contributions signal genuine research depth and reduce perceived risk around visa sponsorship investment.
Prioritize roles requiring a master's or PhD
Positions that explicitly require an advanced degree in a specific technical field are stronger specialty occupation cases for H-1B purposes. Targeting these roles from the start makes the eventual sponsorship pathway more straightforward for both you and your employer.
Prepare your employer for the sponsorship conversation
Many hiring managers are unfamiliar with STEM OPT details. Coming prepared with a clear one-page summary of your authorization timeline, extension eligibility, and H-1B lottery timing removes friction and helps the employer make a faster, more confident decision.
Build relationships within research and ML communities
Referrals dramatically increase your chances at sponsoring employers. Contributing to open-source projects, presenting at workshops, or collaborating on preprints creates professional visibility that often leads to introductions before a role is ever posted publicly.
Machine Learning Scientist jobs are hiring across the US. Find yours.
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Get Access To All JobsFrequently Asked Questions
Can I work as a Machine Learning Scientist on F-1 OPT?
Yes. Machine Learning Scientist is a STEM-designated role, so F-1 students who graduate from a qualifying program in computer science, statistics, or a related field are eligible for both standard 12-month OPT and the 24-month STEM OPT extension, giving you up to 36 months of work authorization total. Your employer must be enrolled in E-Verify to support the STEM extension.
Do Machine Learning Scientist employers commonly sponsor visas?
Sponsorship rates are higher for this role than for most. Machine Learning Scientists are classified as specialty occupation workers under the H-1B, and demand for qualified candidates consistently outpaces supply. Research-intensive employers at large tech companies, AI labs, and well-funded startups sponsor at high rates. Browse verified sponsoring employers on Migrate Mate to narrow your search to companies with a demonstrated track record.
Does my degree field affect OPT eligibility for this role?
It does, particularly for the STEM OPT extension. Your degree must be from STEM-designated CIP code programs, such as computer science, applied mathematics, statistics, or electrical engineering. A degree in a non-STEM field can still support standard 12-month OPT, but the extension requires the STEM designation. The connection between your degree field and the Machine Learning Scientist role also matters for H-1B specialty occupation classification later.
What is the 24-month STEM OPT extension and how does it apply here?
The STEM OPT extension adds 24 months to your standard 12-month OPT period, for a total of 36 months. To qualify, your degree must be in a STEM field, your employer must be enrolled in E-Verify, and you must submit a formal training plan using Form I-983. For Machine Learning Scientists, most roles at qualifying employers meet these requirements. You must apply before your current OPT expires.
What should I expect from the H-1B transition process after OPT?
Most Machine Learning Scientists transition from OPT to H-1B sponsorship. Your employer files an H-1B petition on your behalf, subject to the annual lottery held each April for an October 1 start date. With 36 months of STEM OPT, you have enough runway to enter the lottery up to three times if needed. Your role's advanced degree requirement strengthens the specialty occupation argument, which is one of the more scrutinized parts of the petition.
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