Machine Learning Jobs in USA with Visa Sponsorship
Machine learning roles in the US span academic research labs, big tech research divisions, and applied teams at companies across every industry, all of which regularly sponsor international talent. A strong publication record, conference presentations at venues like NeurIPS or ICML, and demonstrated research contributions significantly strengthen both your job applications and your visa petition. The field rewards deep expertise in areas like deep learning, probabilistic modeling, or optimization, making it one of the most accessible paths for researchers seeking US sponsorship. For detailed occupation requirements, see the O*NET profile.
Find Machine Learning JobsOverview
Showing 5 of 4,165+ Machine Learning jobs
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
See all 4,165+ Machine Learning Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning roles.
Get Access To All JobsINTRODUCTION
BeOne continues to grow at a rapid pace with challenging and exciting opportunities for experienced professionals. When considering candidates, we look for scientific and business professionals who are highly motivated, collaborative, and most importantly, share our passionate interest in fighting cancer.
As a member of the AI expert group, the role will partner with stakeholders across global statistics and data science, clinical development and operation, research, transitional medicine, regulatory, safety, medical writing, digital and technology teams to identify, design and implement AI and machine learning solutions that improve research productivity, development efficiency, and decision making.
ROLE AND RESPONSIBILITIES
Essential Functions of the Job:
- Lead the strategy, design, and implementation of AI and machine learning solutions to support R&D digital transformation and operational efficiency.
- Drive the adoption of AI across R&D by identifying high-impact use cases, building business cases, and partnering with scientific, statistical, clinical, and technology stakeholders.
- Develop and deploy AI/ML models, tools, and platforms that improve the efficiency of digitalization systems, including clinical trial design, clinical data workflows, statistical analysis processes, document generation, knowledge management, and decision-support systems.
- Evaluate emerging AI technologies, including generative AI, large language models, intelligent agents, automation frameworks, and advanced machine learning approaches, and assess their applicability in regulated pharmaceutical R&D environments.
Supervisory Responsibilities:
This is an individual contributor role with significant cross-functional leadership responsibilities. The role does not have direct people management responsibilities at present but may evolve to include supervisory or people-leadership responsibilities as the AI function and portfolio expand.
COMPUTER SKILLS
The candidate should have strong hands-on experience with modern data science, AI, machine learning models, tools and platforms, including:
- Proficiency in programming languages commonly used for data science and AI, such as Python and R.
- Experience with machine learning and deep learning frameworks such as scikit-learn, PyTorch, TensorFlow, or equivalent tools.
- Working knowledge of generative AI, large language models, prompt engineering, retrieval-augmented generation, AI agents, and related application-development frameworks.
- Experience with AI-native programming practices, including the use of AI coding assistants, agentic development tools, prompt-based code generation, automated code review, test generation, documentation generation, and AI-assisted debugging.
- Experience with data manipulation, statistical analysis, visualization, and reporting tools such as SQL, pandas, NumPy, SAS, R Shiny, Power BI, or equivalent platforms.
- Familiarity with cloud-based data and AI platforms, such as AWS, Azure, Databricks.
- Understanding of MLOps, including model development, version control, validation, deployment, monitoring, and lifecycle management.
- Familiarity with data privacy, cybersecurity, access control, audit trail, and documentation requirements in regulated pharmaceutical or healthcare environments.
OTHER QUALIFICATIONS
- Significant experience applying AI, machine learning advanced analytics, or data science in pharmaceutical, biotechnology, healthcare, clinical development, or another regulated environment.
- Demonstrated ability to lead cross-functional initiatives and influence stakeholders across scientific, technical, operational, and leadership teams.
- Knowledge of regulatory expectations, data privacy, model validation, responsible AI, and governance considerations in pharmaceutical R&D.
- Strong problem-solving skills with the ability to translate complex business challenges into practical, scalable AI solutions.
- Excellent communication, presentation, and stakeholder management skills.
EDUCATION REQUIRED
Advanced degrees in statistics, biostatistics, computer science, data science, machine learning, bioinformatics, engineering, mathematics, or related quantitative field. PhD or master’s degree preferred.
TRAVEL:
Willingness to travel domestically within U.S. and occasionally internationally as required to support portfolio governance, stakeholder alignment, and project execution.
BeOne Global Competencies
When we exhibit our values of Patients First, Collaborative Spirit, Bold Ingenuity and Driving Excellence, through our twelve global competencies below, we help get more affordable medicines to more patients around the world.
- Fosters Teamwork
- Provides and Solicits Honest and Actionable Feedback
- Self-Awareness
- Acts Inclusively
- Demonstrates Initiative
- Entrepreneurial Mindset
- Continuous Learning
- Embraces Change
- Results-Oriented
- Analytical Thinking/Data Analysis
- Financial Excellence
- Communicates with Clarity
COMPENSATION
- Salary Range: $158,400.00 - $208,400.00 annually
BeOne is committed to fair and equitable compensation practices. Actual compensation packages are determined by several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, certifications, relevant education or training, and specific work location. Packages may vary by location due to differences in the cost of labor. The recruiter can share more about the specific salary range for a preferred location during the hiring process. Please note that the listed range reflects the base salary or hourly range only. Non-Commercial roles are eligible to participate in the annual bonus plan, and Commercial roles are eligible to participate in an incentive compensation plan. All Company employees have the opportunity to own shares of BeOne Medicines Ltd. stock because all employees are eligible for discretionary equity awards and to voluntarily participate in the Employee Stock Purchase Plan. The Company has a comprehensive benefits package that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness.
We are proud to be an equal opportunity employer. BeOne does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, disability, national origin, veteran status or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need. In order to ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Era Veterans’ Readjustment Assistance Act of 1974, Title I of the Americans with Disabilities Act of 1990, and any other applicable federal, state or local laws, applicants who require reasonable accommodation in the job application process may contact accommodationsus@beonemed.com.
INTRODUCTION
BeOne continues to grow at a rapid pace with challenging and exciting opportunities for experienced professionals. When considering candidates, we look for scientific and business professionals who are highly motivated, collaborative, and most importantly, share our passionate interest in fighting cancer.
As a member of the AI expert group, the role will partner with stakeholders across global statistics and data science, clinical development and operation, research, transitional medicine, regulatory, safety, medical writing, digital and technology teams to identify, design and implement AI and machine learning solutions that improve research productivity, development efficiency, and decision making.
ROLE AND RESPONSIBILITIES
Essential Functions of the Job:
- Lead the strategy, design, and implementation of AI and machine learning solutions to support R&D digital transformation and operational efficiency.
- Drive the adoption of AI across R&D by identifying high-impact use cases, building business cases, and partnering with scientific, statistical, clinical, and technology stakeholders.
- Develop and deploy AI/ML models, tools, and platforms that improve the efficiency of digitalization systems, including clinical trial design, clinical data workflows, statistical analysis processes, document generation, knowledge management, and decision-support systems.
- Evaluate emerging AI technologies, including generative AI, large language models, intelligent agents, automation frameworks, and advanced machine learning approaches, and assess their applicability in regulated pharmaceutical R&D environments.
Supervisory Responsibilities:
This is an individual contributor role with significant cross-functional leadership responsibilities. The role does not have direct people management responsibilities at present but may evolve to include supervisory or people-leadership responsibilities as the AI function and portfolio expand.
COMPUTER SKILLS
The candidate should have strong hands-on experience with modern data science, AI, machine learning models, tools and platforms, including:
- Proficiency in programming languages commonly used for data science and AI, such as Python and R.
- Experience with machine learning and deep learning frameworks such as scikit-learn, PyTorch, TensorFlow, or equivalent tools.
- Working knowledge of generative AI, large language models, prompt engineering, retrieval-augmented generation, AI agents, and related application-development frameworks.
- Experience with AI-native programming practices, including the use of AI coding assistants, agentic development tools, prompt-based code generation, automated code review, test generation, documentation generation, and AI-assisted debugging.
- Experience with data manipulation, statistical analysis, visualization, and reporting tools such as SQL, pandas, NumPy, SAS, R Shiny, Power BI, or equivalent platforms.
- Familiarity with cloud-based data and AI platforms, such as AWS, Azure, Databricks.
- Understanding of MLOps, including model development, version control, validation, deployment, monitoring, and lifecycle management.
- Familiarity with data privacy, cybersecurity, access control, audit trail, and documentation requirements in regulated pharmaceutical or healthcare environments.
OTHER QUALIFICATIONS
- Significant experience applying AI, machine learning advanced analytics, or data science in pharmaceutical, biotechnology, healthcare, clinical development, or another regulated environment.
- Demonstrated ability to lead cross-functional initiatives and influence stakeholders across scientific, technical, operational, and leadership teams.
- Knowledge of regulatory expectations, data privacy, model validation, responsible AI, and governance considerations in pharmaceutical R&D.
- Strong problem-solving skills with the ability to translate complex business challenges into practical, scalable AI solutions.
- Excellent communication, presentation, and stakeholder management skills.
EDUCATION REQUIRED
Advanced degrees in statistics, biostatistics, computer science, data science, machine learning, bioinformatics, engineering, mathematics, or related quantitative field. PhD or master’s degree preferred.
TRAVEL:
Willingness to travel domestically within U.S. and occasionally internationally as required to support portfolio governance, stakeholder alignment, and project execution.
BeOne Global Competencies
When we exhibit our values of Patients First, Collaborative Spirit, Bold Ingenuity and Driving Excellence, through our twelve global competencies below, we help get more affordable medicines to more patients around the world.
- Fosters Teamwork
- Provides and Solicits Honest and Actionable Feedback
- Self-Awareness
- Acts Inclusively
- Demonstrates Initiative
- Entrepreneurial Mindset
- Continuous Learning
- Embraces Change
- Results-Oriented
- Analytical Thinking/Data Analysis
- Financial Excellence
- Communicates with Clarity
COMPENSATION
- Salary Range: $158,400.00 - $208,400.00 annually
BeOne is committed to fair and equitable compensation practices. Actual compensation packages are determined by several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, certifications, relevant education or training, and specific work location. Packages may vary by location due to differences in the cost of labor. The recruiter can share more about the specific salary range for a preferred location during the hiring process. Please note that the listed range reflects the base salary or hourly range only. Non-Commercial roles are eligible to participate in the annual bonus plan, and Commercial roles are eligible to participate in an incentive compensation plan. All Company employees have the opportunity to own shares of BeOne Medicines Ltd. stock because all employees are eligible for discretionary equity awards and to voluntarily participate in the Employee Stock Purchase Plan. The Company has a comprehensive benefits package that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness.
We are proud to be an equal opportunity employer. BeOne does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, disability, national origin, veteran status or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need. In order to ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Era Veterans’ Readjustment Assistance Act of 1974, Title I of the Americans with Disabilities Act of 1990, and any other applicable federal, state or local laws, applicants who require reasonable accommodation in the job application process may contact accommodationsus@beonemed.com.
See all 4,165+ Machine Learning Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning roles.
Get Access To All JobsTips for Finding Machine Learning Jobs
Leverage top-tier publications for an O-1 visa
Papers accepted at NeurIPS, ICML, ICLR, or CVPR carry significant weight in an O-1 extraordinary ability petition. Combine publications with citation counts, peer review invitations, and conference keynotes to build a compelling case.
Explore EB-2 NIW if you hold a PhD in ML
ML researchers with doctoral degrees can petition for an EB-2 National Interest Waiver without employer sponsorship. If your work has applications in healthcare, climate, defense, or other areas of national importance, NIW may be a viable green card path.
Target industries beyond big tech
ML talent is in demand in quantitative finance (Two Sigma, Citadel, DE Shaw), pharmaceuticals (Pfizer, Genentech), and autonomous vehicles (Waymo). These industries sponsor aggressively and often pay competitively with major tech companies.
Use cap-exempt positions at national labs
Sandia, Los Alamos, and Oak Ridge National Laboratories run active ML research programs with H-1B cap-exempt positions. No lottery required, and you can file any time of year while working on cutting-edge problems.
Build a strong STEM OPT runway
CS, mathematics, and statistics degrees qualify for STEM OPT - up to 3 years of work authorization. Use that time to publish, contribute to production ML systems, and establish the track record that makes your employer invest in long-term sponsorship.
Highlight your engineering skills alongside research
Employers sponsoring ML roles want candidates who can move models from notebooks to production. Proficiency in PyTorch, distributed training, and ML infrastructure makes you more valuable and strengthens the case for a technical specialty occupation.
Frequently Asked Questions
How important is a publication record for getting sponsored in a machine learning role?
Publications are highly important for research-focused ML roles at organizations like Google DeepMind, Meta FAIR, or university labs. For H-1B visa purposes, they demonstrate specialized knowledge at the level expected of a degree holder. For O-1 visa petitions, publications are one of the core criteria for extraordinary ability. Applied ML roles at companies focused on deploying existing techniques may prioritize engineering skills over publications, so the importance depends on whether the role is research or production-oriented.
Can I transition from academia to an industry ML role in the U.S., and will employers sponsor that transition?
Yes. The academic-to-industry transition is one of the most well-established paths in machine learning. Companies like Google, Meta, Microsoft, and Amazon have research scientist roles specifically designed for people with academic backgrounds and routinely sponsor H-1B and O-1 visas for these hires. If you are currently a postdoc or researcher at a U.S. university, you may already have J-1 visa or H-1B status that can be transferred to an industry employer. Connect your academic work to practical applications during interviews to show awareness of production constraints.
How to find Machine Learning jobs with visa sponsorship?
To find Machine Learning 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 sponsor H-1B, O-1, or TN visas for ML engineers, data scientists, and AI researchers. These employers actively seek skilled professionals in machine learning, deep learning, and artificial intelligence roles.
Does the O-1 visa work well for ML researchers?
Yes, the O-1A is one of the strongest visa pathways for ML researchers with solid track records. Published papers at top venues (NeurIPS, ICML, ICLR, CVPR), peer review service for journals and conferences, high citation counts, and significant open-source contributions can all serve as evidence of extraordinary ability. The O-1 has no annual cap and no lottery, and it can be processed in 15 business days with premium processing. Many top AI labs actively support O-1 applications for research hires.
Which ML specializations are most in demand for visa sponsorship?
Large language models, reinforcement learning, and computer vision remain the highest-demand specializations. Emerging areas like geometric deep learning, causal ML, and efficient model architectures are particularly valuable for immigration purposes because the talent pool is extremely small. USCIS evaluates whether the role requires someone with your specific expertise, and niche specializations make that argument easier. Applied specializations like recommendation systems, search ranking, and fraud detection are also heavily sponsored.
Do open-source contributions to ML libraries help with visa petitions?
Yes, particularly for O-1 petitions where they can serve as evidence of original contributions of major significance to the field. Contributions to widely used frameworks like PyTorch, TensorFlow, Hugging Face Transformers, or scikit-learn carry the most weight. Document your contributions with metrics: download counts, GitHub stars, citations in papers, and adoption by major companies. For H-1B petitions, open-source work is less directly relevant but helps demonstrate the specialized depth of your expertise.
What is the prevailing wage requirement for sponsored Machine Learning 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 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.