Machine Learning Engineer Jobs in USA with Visa Sponsorship
Machine learning engineers who build the infrastructure to train, deploy, and monitor ML models at scale are critically needed by US companies operationalizing their data science investments. This role sits at the intersection of software engineering and data science - requiring expertise in feature engineering, model serving, distributed training, and monitoring - which makes it a strong specialty occupation for visa sponsorship. Employers ranging from FAANG to fintech to healthcare AI companies sponsor machine learning engineers because reliable ML infrastructure is what turns experimental models into revenue-generating products. For detailed occupation requirements, see the O*NET profile.
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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.
Senior ML/Gen AI Engineer
Introduction to the Team:
Expedia Technology teams partner with our Product teams to create innovative products, services, and tools to deliver high-quality experiences for travelers, partners, and our employees. A singular technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction.
We are the Strategic Partnerships & Affiliates team in the Expedia Product & Technology division of Expedia Group. We are building the next-generation, scalable B2B partnership platform that will power hundreds of thousands of demand partners across the industry ranging from big businesses and Enterprises to small bloggers, micro influencers and creators in helping them recommend Expedia Group brands to their audiences and in the process grow their businesses. We aim to redefine the travel partnerships sector by building innovative partner tools and solutions that incorporates the new ways in which today’s travelers discover and shop travel products. To do this, we need technically passionate engineers with an entrepreneurial approach who love challenges, enjoy problem solving and take pride in delivering best-in-class products. You will work with a geo-distributed, cross functional team of 50+ engineers designing and developing solutions for complex problems with a wide-reaching business impact.
In this role, you will:
- Collaborate closely with ML Scientists to productize and scale ML models, from experimentation to robust production systems
- Design, build, and own large-scale, distributed machine learning systems for training, deployment, inference, and monitoring
- Lead design discussions and architecture reviews; drive high-impact engineering decisions for ML platforms and applications
- Mentor and coach junior engineers and peers on best practices in ML engineering, system design, and code quality
- Develop and maintain reusable components, libraries, and tools to accelerate ML development lifecycle
- Proactively identify areas for improvement in model performance, pipeline efficiency, data quality, or platform capabilities
- Ensure scalability, observability, and fault-tolerance across all components of the ML stack
- Promote engineering excellence by advocating for best practices in testing, CI/CD, infrastructure-as-code, and monitoring
- Partner with stakeholders across Data Engineering, Product, Marketing, and Platform teams to align solutions with business goals
- Stay up to date on advancements in MLOps, ML frameworks, distributed systems, and apply learnings to improve systems and processes
Minimum Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
- 8+ years of experience in software/ML engineering with a proven track record of delivering ML solutions at scale
- Strong programming skills in modern languages such as Python, Scala, or Java
- Deep experience in building and maintaining production-grade ML pipelines and infrastructure
- Expertise in MLOps practices, including model lifecycle management, versioning, monitoring, and CI/CD for ML
- Experience with big data ecosystems (e.g., Spark, Hive, Databricks, Delta Lake) and streaming technologies
- Proficient in working with ML frameworks like TensorFlow, PyTorch, XGBoost, or similar
- Experience working in cloud-based environments (AWS, GCP, or Azure) and with infrastructure-as-code tools
- Hands-on experience with orchestration tools like Flyte, Airflow, Kubeflow, etc.
- Proficient in containerization and orchestration technologies like Docker and Kubernetes
Preferred Qualifications:
- Familiarity with advanced ML techniques, including deep learning, NLP, recommendation systems, and generative AI
- Experience designing or implementing multi-agent architectures for autonomous collaboration and decision-making
- Understanding of agent planning, memory, tool use, and self-reflection mechanisms
- Experience building basic ML models
- Experience with automated testing across different layers (unit, integration, functional)
The total cash range for this position in Seattle is $184,500.00 to $258,000.00. Employees in this role have the potential to increase their pay up to $295,000.00, 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 $199,000.00 to $278,500.00. Employees in this role have the potential to increase their pay up to $318,500.00, 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.
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.
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, veteran status, or any other characteristic protected by law. 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.
Senior ML/Gen AI Engineer
Introduction to the Team:
Expedia Technology teams partner with our Product teams to create innovative products, services, and tools to deliver high-quality experiences for travelers, partners, and our employees. A singular technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction.
We are the Strategic Partnerships & Affiliates team in the Expedia Product & Technology division of Expedia Group. We are building the next-generation, scalable B2B partnership platform that will power hundreds of thousands of demand partners across the industry ranging from big businesses and Enterprises to small bloggers, micro influencers and creators in helping them recommend Expedia Group brands to their audiences and in the process grow their businesses. We aim to redefine the travel partnerships sector by building innovative partner tools and solutions that incorporates the new ways in which today’s travelers discover and shop travel products. To do this, we need technically passionate engineers with an entrepreneurial approach who love challenges, enjoy problem solving and take pride in delivering best-in-class products. You will work with a geo-distributed, cross functional team of 50+ engineers designing and developing solutions for complex problems with a wide-reaching business impact.
In this role, you will:
- Collaborate closely with ML Scientists to productize and scale ML models, from experimentation to robust production systems
- Design, build, and own large-scale, distributed machine learning systems for training, deployment, inference, and monitoring
- Lead design discussions and architecture reviews; drive high-impact engineering decisions for ML platforms and applications
- Mentor and coach junior engineers and peers on best practices in ML engineering, system design, and code quality
- Develop and maintain reusable components, libraries, and tools to accelerate ML development lifecycle
- Proactively identify areas for improvement in model performance, pipeline efficiency, data quality, or platform capabilities
- Ensure scalability, observability, and fault-tolerance across all components of the ML stack
- Promote engineering excellence by advocating for best practices in testing, CI/CD, infrastructure-as-code, and monitoring
- Partner with stakeholders across Data Engineering, Product, Marketing, and Platform teams to align solutions with business goals
- Stay up to date on advancements in MLOps, ML frameworks, distributed systems, and apply learnings to improve systems and processes
Minimum Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
- 8+ years of experience in software/ML engineering with a proven track record of delivering ML solutions at scale
- Strong programming skills in modern languages such as Python, Scala, or Java
- Deep experience in building and maintaining production-grade ML pipelines and infrastructure
- Expertise in MLOps practices, including model lifecycle management, versioning, monitoring, and CI/CD for ML
- Experience with big data ecosystems (e.g., Spark, Hive, Databricks, Delta Lake) and streaming technologies
- Proficient in working with ML frameworks like TensorFlow, PyTorch, XGBoost, or similar
- Experience working in cloud-based environments (AWS, GCP, or Azure) and with infrastructure-as-code tools
- Hands-on experience with orchestration tools like Flyte, Airflow, Kubeflow, etc.
- Proficient in containerization and orchestration technologies like Docker and Kubernetes
Preferred Qualifications:
- Familiarity with advanced ML techniques, including deep learning, NLP, recommendation systems, and generative AI
- Experience designing or implementing multi-agent architectures for autonomous collaboration and decision-making
- Understanding of agent planning, memory, tool use, and self-reflection mechanisms
- Experience building basic ML models
- Experience with automated testing across different layers (unit, integration, functional)
The total cash range for this position in Seattle is $184,500.00 to $258,000.00. Employees in this role have the potential to increase their pay up to $295,000.00, 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 $199,000.00 to $278,500.00. Employees in this role have the potential to increase their pay up to $318,500.00, 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.
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.
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, veteran status, or any other characteristic protected by law. 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.
See all 4,050+ Machine Learning Engineer Jobs
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Get Access To All JobsTips for Finding Visa Sponsorship as a Machine Learning Engineer
Emphasize production engineering over research
MLE roles focus on deploying, scaling, and monitoring models in production - not just training them. Highlight experience with model serving frameworks like TensorFlow Serving, TorchServe, or Triton Inference Server to stand out.
Target companies with mature ML infrastructure teams
Google, Meta, Netflix, Uber, and Spotify have dedicated MLE teams that build and maintain production ML systems. These companies sponsor H-1B petitions under SOC 15-1252 and understand the engineering nature of the role.
Leverage your dual skill set in interviews
The MLE role bridges data science and software engineering, and that's your selling point. Strong candidates can discuss both model optimization and system design, which is rare and makes employers more willing to invest in sponsorship.
Build MLOps expertise to increase your value
Feature stores, experiment tracking, model monitoring, and automated retraining pipelines are critical MLE skills. Companies building serious ML products need engineers who can operationalize models, not just build prototypes.
Use STEM OPT to prove production reliability
With a STEM-eligible degree, you get up to 3 years of work authorization through OPT. ML systems require deep institutional knowledge to maintain - use that time to become indispensable to your team's production stack.
File under the right SOC code for engineering
MLE roles typically file under SOC 15-1252 (Software Developers), emphasizing the engineering and systems side of the work. This classification has strong precedent for H-1B approval - ensure your job description reflects the production engineering focus.
Frequently Asked Questions
What ML infrastructure skills are most valued by employers sponsoring machine learning engineers?
Experience with distributed training frameworks (PyTorch Distributed, DeepSpeed), model serving platforms (TensorFlow Serving, NVIDIA Triton, ONNX Runtime), and feature engineering tools (Feast, Tecton) are the most sought-after skills. Knowledge of GPU cluster management, inference cost optimization, and monitoring for data drift also carries significant weight. These specific technical requirements are exactly what make the visa petition strong, because they show the role requires specialized knowledge beyond general software engineering.
Do machine learning engineers need a PhD, or is a master's degree sufficient for sponsorship?
A master's degree is sufficient for the vast majority of ML engineering roles, and many positions only require a bachelor's in computer science or a related field. A PhD is more commonly expected for research-focused ML positions, not engineering roles focused on production systems. That said, a master's degree qualifies you for the additional 20,000 H-1B visa cap exemption slots reserved for U.S. advanced degree holders, which improves your lottery odds.
I have a research background but want to move into ML engineering. How does this affect sponsorship?
The transition is common and does not create visa issues. Your research background demonstrates the theoretical knowledge needed to make sound infrastructure decisions, while any production-adjacent work from your research (deploying models, building data pipelines, optimizing training runs) shows practical engineering capability. If you have a PhD, you benefit from the advanced degree H-1B exemption. The combination of theoretical depth from research and hands-on engineering skills can actually strengthen your petition.
How to find Machine Learning Engineer jobs with visa sponsorship?
To find Machine Learning Engineer jobs with visa sponsorship, use Migrate Mate, which specializes in connecting international talent with sponsoring employers. Focus on tech companies, startups, and research institutions that commonly hire ML engineers on H-1B, O-1 visa, or other work visas. These employers often need specialized AI/ML expertise and are willing to sponsor qualified candidates with relevant experience in data science, neural networks, and algorithm development.
Which companies sponsor machine learning engineers most actively?
Companies operationalizing ML at scale are the most active sponsors. This includes large tech firms (Google, Meta, Amazon, Microsoft), ML-first product companies (Spotify, Netflix, Uber, Stripe), and AI infrastructure startups (Databricks, Anyscale, Weights & Biases). Fintech and healthcare AI companies are also growing sponsors. Look for employers whose products depend on reliable ML systems in production, as they are most motivated to invest in sponsorship for engineers who can bridge the gap between a trained model and a live product.
What prevailing wage levels typically apply to ML engineering roles?
ML engineering salaries typically place candidates at Level 3 or Level 4 of the Department of Labor prevailing wage system, which is favorable for visa petitions. Higher wage levels signal to USCIS that the role is senior and specialized, reducing the risk of a Request for Evidence. If an employer offers a salary at Level 1, that is a red flag for both immigration risk and fair compensation. You can check prevailing wages for your role and location on the DOL's Foreign Labor Certification Data Center.
What is the prevailing wage requirement for sponsored Machine Learning Engineer jobs?
When a U.S. employer sponsors a foreign worker for a work visa, they are legally required to pay at least the "prevailing wage", the average wage paid to workers in the same occupation, in the same geographic area, with similar experience. This is set by the Department of Labor to prevent employers from hiring foreign workers at below-market rates. The prevailing wage varies significantly by role, location, and experience level. For example, a machine learning engineer in California will have a different prevailing wage than the same role in a smaller state. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search Page.