Machine Learning Engineer Jobs at Microsoft with Visa Sponsorship
Microsoft builds some of its most ambitious AI and ML systems through Machine Learning Engineer roles spanning research, applied science, and production infrastructure. The company has a well-established sponsorship process across multiple visa categories, making it a realistic target for international candidates at all career stages.
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As Microsoft continues to push the boundaries of AI, we are on the lookout for passionate individuals to work with us on the most interesting and challenging AI questions of our time. Our vision is bold and broad — to build systems that have true artificial intelligence across agents, applications, services, and infrastructure. It’s also inclusive: we aim to make AI accessible to all — consumers, businesses, developers — so that everyone can realize its benefits. Microsoft AI (MAI) is looking for a talented and experienced Machine Learning Engineer to join our Growth team and help shape the next generation of AI systems, specifically for our personal AI assistant, Copilot. This role focuses on optimizing user engagement, retention, and personalization with innovative AI solutions, with a strong preference for expertise in recommendation systems and feed algorithms. However, we also welcome candidates with broader machine learning experience and a passion for solving dynamic AI challenges. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. This expectation is subject to local law and may vary by jurisdiction.
Responsibilities
- Develop and Deploy Models: Design, develop, and implement machine learning models for high-performance recommendation systems and personalized feeds. Candidates without direct experience in recommendations and ranking are still encouraged to apply if they possess exceptional technical skills in other areas of machine learning.
- Large Language Model Expertise: Leverage large language models (LLMs) to create scalable, intelligent solutions for content understanding, user engagement, and relevance ranking.
- Experimentation and Analysis: Drive data-driven experimentation using A/B testing, advanced analytics, and statistical techniques to identify growth opportunities and refine algorithms.
- Infrastructure Optimization: Develop and optimize pipelines, tools, and infrastructure to support real-time decision-making, personalization, and predictive analytics.
- Technical Leadership: Mentor team members and foster collaboration within cross-functional teams, including engineers, product managers, and designers.
- Continuous Innovation: Stay informed on emerging trends in AI and machine learning, and integrate them to drive innovation and improve product offerings.
- Cross-functional Collaboration: Articulate findings and recommendations to technical and non-technical audiences, influencing decisions across teams and leadership.
- Embody our Culture and Values.
Qualifications
Required Qualifications
- Bachelor's Degree in Computer Science, or related technical discipline AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
Preferred Qualifications
- 3+ years of experience building and deploying ML models in production environments.
- Strong coding skills in Python and experience with ML frameworks (e.g., PyTorch, TensorFlow).
- Familiarity with data processing tools (e.g., Spark, Pandas) and cloud platforms (e.g., Azure, AWS).
- Experience with classification, recommendation, or personalization systems.
- Experience using large language models (LLMs) for machine learning and AI applications.
- Hands-on experience in growth engineering, driving improvements in user acquisition, engagement, and retention.
- Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Expertise in personalization strategies and user behavior modeling.
- Strong problem-solving skills and the ability to independently design solutions to complex challenges.
- Excellent communication skills, with the ability to influence technical and non-technical audiences.
- Ability to work in a fast-paced environment, manage multiple priorities, and adapt to changing requirements and deadlines.
Compensation
Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay
Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances.
If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
Overview
As Microsoft continues to push the boundaries of AI, we are on the lookout for passionate individuals to work with us on the most interesting and challenging AI questions of our time. Our vision is bold and broad — to build systems that have true artificial intelligence across agents, applications, services, and infrastructure. It’s also inclusive: we aim to make AI accessible to all — consumers, businesses, developers — so that everyone can realize its benefits. Microsoft AI (MAI) is looking for a talented and experienced Machine Learning Engineer to join our Growth team and help shape the next generation of AI systems, specifically for our personal AI assistant, Copilot. This role focuses on optimizing user engagement, retention, and personalization with innovative AI solutions, with a strong preference for expertise in recommendation systems and feed algorithms. However, we also welcome candidates with broader machine learning experience and a passion for solving dynamic AI challenges. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. This expectation is subject to local law and may vary by jurisdiction.
Responsibilities
- Develop and Deploy Models: Design, develop, and implement machine learning models for high-performance recommendation systems and personalized feeds. Candidates without direct experience in recommendations and ranking are still encouraged to apply if they possess exceptional technical skills in other areas of machine learning.
- Large Language Model Expertise: Leverage large language models (LLMs) to create scalable, intelligent solutions for content understanding, user engagement, and relevance ranking.
- Experimentation and Analysis: Drive data-driven experimentation using A/B testing, advanced analytics, and statistical techniques to identify growth opportunities and refine algorithms.
- Infrastructure Optimization: Develop and optimize pipelines, tools, and infrastructure to support real-time decision-making, personalization, and predictive analytics.
- Technical Leadership: Mentor team members and foster collaboration within cross-functional teams, including engineers, product managers, and designers.
- Continuous Innovation: Stay informed on emerging trends in AI and machine learning, and integrate them to drive innovation and improve product offerings.
- Cross-functional Collaboration: Articulate findings and recommendations to technical and non-technical audiences, influencing decisions across teams and leadership.
- Embody our Culture and Values.
Qualifications
Required Qualifications
- Bachelor's Degree in Computer Science, or related technical discipline AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
Preferred Qualifications
- 3+ years of experience building and deploying ML models in production environments.
- Strong coding skills in Python and experience with ML frameworks (e.g., PyTorch, TensorFlow).
- Familiarity with data processing tools (e.g., Spark, Pandas) and cloud platforms (e.g., Azure, AWS).
- Experience with classification, recommendation, or personalization systems.
- Experience using large language models (LLMs) for machine learning and AI applications.
- Hands-on experience in growth engineering, driving improvements in user acquisition, engagement, and retention.
- Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Expertise in personalization strategies and user behavior modeling.
- Strong problem-solving skills and the ability to independently design solutions to complex challenges.
- Excellent communication skills, with the ability to influence technical and non-technical audiences.
- Ability to work in a fast-paced environment, manage multiple priorities, and adapt to changing requirements and deadlines.
Compensation
Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay
Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances.
If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
See all 65+ Machine Learning Engineer at Microsoft jobs
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Get Access To All JobsTips for Finding Machine Learning Engineer Jobs at Microsoft Jobs
Align your portfolio to Microsoft's ML stack
Microsoft's ML engineering roles frequently involve PyTorch, Azure ML, and large-scale distributed training. Documenting hands-on work with these tools in your GitHub or portfolio gives hiring managers immediate evidence your background fits their production environment.
Target teams hiring through multiple visa pathways
Microsoft sponsors H-1B, E-3, and H-1B1 visas, so Australian and Singapore nationals have cap-exempt options that bypass the H-1B lottery. Identifying which pathway applies to your citizenship before applying lets you frame your timeline accurately during offer negotiations.
Use Migrate Mate to surface active ML openings
Microsoft posts Machine Learning Engineer roles across dozens of product teams simultaneously. Use Migrate Mate to filter verified sponsorship-eligible openings so you're applying to positions where your visa type is already anticipated by the hiring team.
Prepare your credentials before the offer stage
Microsoft's immigration team initiates LCA filing with the DOL shortly after an offer is accepted. Having your academic transcripts evaluated for U.S. equivalency in advance, especially if you hold a three-year degree, prevents delays once the process starts.
Understand Microsoft's transfer options if lottery misses
If you're already at Microsoft on an H-1B and miss a lottery cycle, the company can file under cap-exempt provisions for employees continuing in the same role. Confirm your eligibility window with your assigned immigration counsel before your current status expires.
Negotiate your start date around USCIS premium processing
H-1B approvals under standard processing can take several months. Microsoft commonly uses premium processing for time-sensitive hires, but confirming this expectation during offer negotiation lets you set a start date that won't require you to be out of status.
Machine Learning Engineer at Microsoft jobs are hiring across the US. Find yours.
Find Machine Learning Engineer at Microsoft JobsFrequently Asked Questions
Does Microsoft sponsor H-1B visas for Machine Learning Engineers?
Yes, Microsoft sponsors H-1B visas for Machine Learning Engineer roles. The company participates in the annual H-1B lottery for cap-subject candidates and also supports cap-exempt filings in qualifying situations. Microsoft works with in-house immigration counsel to manage the LCA filing with the DOL and the subsequent I-129 petition with USCIS, so the process is well-structured once you receive an offer.
How do I apply for Machine Learning Engineer jobs at Microsoft?
Applications go through Microsoft's careers portal, where ML roles are listed by product team, seniority level, and location. Most positions require a technical screen followed by a multi-round virtual loop covering ML fundamentals, system design, and coding. You can also browse verified sponsorship-eligible Machine Learning Engineer openings at Microsoft through Migrate Mate, which filters roles where international candidates are actively considered.
Which visa types does Microsoft typically use for Machine Learning Engineers?
Microsoft sponsors H-1B visas for most international Machine Learning Engineer hires. Australian citizens can pursue the E-3 visa, which has a separate annual allocation and avoids the H-1B lottery entirely. Singapore nationals working in specialty occupations may qualify for the H-1B1. For longer-term pathways, Microsoft also supports EB-2 and EB-3 Green Card sponsorship for employees who have established tenure in the role.
What qualifications does Microsoft expect for Machine Learning Engineer roles?
Most Machine Learning Engineer positions at Microsoft expect a bachelor's degree or higher in computer science, electrical engineering, statistics, or a closely related field. In practice, roles on applied AI teams tend to favor candidates with direct experience training and deploying large models, proficiency with distributed computing frameworks, and familiarity with cloud infrastructure, particularly Azure. Research-oriented roles often expect graduate-level credentials or published work.
How long does the sponsorship process typically take after an offer from Microsoft?
After you accept an offer, Microsoft's immigration team files the Labor Condition Application with the DOL, which is typically certified within seven business days. The I-129 petition to USCIS follows, with standard processing taking several months and premium processing resolving in roughly 15 business days. H-1B cap-subject hires must also account for the lottery cycle, meaning an October 1 start date is the earliest possible for new cap-subject approvals.
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