AI Engineer Jobs at Microsoft with Visa Sponsorship
Microsoft builds AI Engineer roles around large-scale systems work, from foundation model development to production inference infrastructure. The company has a long track record of sponsoring work visas across multiple categories, making it a realistic target for international candidates with strong ML and systems engineering backgrounds.
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Overview
We’re hiring a Senior Applied AI Engineer, Image Generation to join a fast‑moving, high‑ownership team building next‑generation AI assistant and productivity capabilities. This role blends LLM product engineering, evaluation science, hillclimbing, and internal tool building with the pace and creativity of a startup.
The primary focus for this role will be on building the best image generation product out there. You'll get to experiment with all sorts of models from open source to SOTA developed at Microsoft. You'll work through some of the most challenging multimodal problems that exist today while shipping improvements to customers daily.
Responsibilities
Model Development & Training
- Train, fine-tune, and evaluate image generation models (diffusion, GAN, transformer-based)
- Implement and adapt techniques from research papers into working production systems
- Design and run experiments to improve image quality, diversity, and controllability
- Curate, clean, and manage large-scale image-text training datasets
Evaluation, Hillclimbing & Quality Systems
Build and maintain evaluation frameworks for correctness, safety, grounding, and UX quality.
- Run hillclimbing loops across prompts, models, and tool-use strategies to continuously improve assistant performance.
- Analyze failure modes, design mitigations, and drive systematic improvements across the stack.
LLM Tooling & Internal Infrastructure
- Develop internal tools for prompt experimentation, model comparison telemetry and debugging automated eval pipelines
- Create reusable frameworks that accelerate the entire AI org’s ability to ship high-quality assistant features.
Applied ML & Product Integration
- Integrate LLMs with product surfaces, APIs, and backend systems.
- Build lightweight ML components (ranking, classification, summarization, personalization) that enhance assistant intelligence.
- Collaborate with PM, design, and research to turn ambiguous ideas into polished user experiences.
High-Velocity Teamwork
Operate with startup-founder energy: bias for action, rapid iteration, and comfort with ambiguity.
- Work closely with researchers, engineers, and product leaders in a fast-moving AI team where ideas ship quickly and impact is immediate.
- Contribute to a culture of experimentation, clarity, and high-quality execution.
- Build prompt architectures, system instructions, and orchestration logic that ensure reliability, grounding, and personality consistency.
- Prototype new capabilities rapidly and iterate based on user signals and evaluation data.
Production & Infrastructure
- Optimize models for inference latency, throughput, and cost (quantization, distillation, batching)
- Build and maintain serving pipelines for real-time and batch image generation
- Develop APIs and SDKs that expose image generation capabilities to downstream teams/products
- Monitor model performance in production; debug quality regressions
Qualifications
Required Qualifications
- Bachelor's Degree in Computer Science or related technical field 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
- Master’s Degree AND 3+ years of experience in engineering, problem solving, model building, evaluation, data analysis OR equivalent experience.
- PhD in engineering, applied math, statistics, or related analytical field.
- 2+ years shipping production-level code, models, or data analysis.
- 1+ years using AI-assisted coding and analysis techniques.
- Solid grasp of deep learning: loss functions, optimization, regularization, training stability
- Experience deploying ML models at scale (inference optimization, quantization, distillation)
- Familiarity with image preprocessing pipelines, data augmentation, and dataset curation
- Experience working on small teams and mid-stage startup environments.
- Experience working on AI products.
- 4+ years shipping production-level code, models, or data analysis.
- Deep experience building from zero-to-one.
- Experience with RLHF / DPO for aligning image models to human preferences
- Knowledge of safety/content filtering for generated images
- Hands on work hillclimbing AI evaluations.
Compensation
-
Data Science 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.
-
Data Science 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:
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.

Overview
We’re hiring a Senior Applied AI Engineer, Image Generation to join a fast‑moving, high‑ownership team building next‑generation AI assistant and productivity capabilities. This role blends LLM product engineering, evaluation science, hillclimbing, and internal tool building with the pace and creativity of a startup.
The primary focus for this role will be on building the best image generation product out there. You'll get to experiment with all sorts of models from open source to SOTA developed at Microsoft. You'll work through some of the most challenging multimodal problems that exist today while shipping improvements to customers daily.
Responsibilities
Model Development & Training
- Train, fine-tune, and evaluate image generation models (diffusion, GAN, transformer-based)
- Implement and adapt techniques from research papers into working production systems
- Design and run experiments to improve image quality, diversity, and controllability
- Curate, clean, and manage large-scale image-text training datasets
Evaluation, Hillclimbing & Quality Systems
Build and maintain evaluation frameworks for correctness, safety, grounding, and UX quality.
- Run hillclimbing loops across prompts, models, and tool-use strategies to continuously improve assistant performance.
- Analyze failure modes, design mitigations, and drive systematic improvements across the stack.
LLM Tooling & Internal Infrastructure
- Develop internal tools for prompt experimentation, model comparison telemetry and debugging automated eval pipelines
- Create reusable frameworks that accelerate the entire AI org’s ability to ship high-quality assistant features.
Applied ML & Product Integration
- Integrate LLMs with product surfaces, APIs, and backend systems.
- Build lightweight ML components (ranking, classification, summarization, personalization) that enhance assistant intelligence.
- Collaborate with PM, design, and research to turn ambiguous ideas into polished user experiences.
High-Velocity Teamwork
Operate with startup-founder energy: bias for action, rapid iteration, and comfort with ambiguity.
- Work closely with researchers, engineers, and product leaders in a fast-moving AI team where ideas ship quickly and impact is immediate.
- Contribute to a culture of experimentation, clarity, and high-quality execution.
- Build prompt architectures, system instructions, and orchestration logic that ensure reliability, grounding, and personality consistency.
- Prototype new capabilities rapidly and iterate based on user signals and evaluation data.
Production & Infrastructure
- Optimize models for inference latency, throughput, and cost (quantization, distillation, batching)
- Build and maintain serving pipelines for real-time and batch image generation
- Develop APIs and SDKs that expose image generation capabilities to downstream teams/products
- Monitor model performance in production; debug quality regressions
Qualifications
Required Qualifications
- Bachelor's Degree in Computer Science or related technical field 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
- Master’s Degree AND 3+ years of experience in engineering, problem solving, model building, evaluation, data analysis OR equivalent experience.
- PhD in engineering, applied math, statistics, or related analytical field.
- 2+ years shipping production-level code, models, or data analysis.
- 1+ years using AI-assisted coding and analysis techniques.
- Solid grasp of deep learning: loss functions, optimization, regularization, training stability
- Experience deploying ML models at scale (inference optimization, quantization, distillation)
- Familiarity with image preprocessing pipelines, data augmentation, and dataset curation
- Experience working on small teams and mid-stage startup environments.
- Experience working on AI products.
- 4+ years shipping production-level code, models, or data analysis.
- Deep experience building from zero-to-one.
- Experience with RLHF / DPO for aligning image models to human preferences
- Knowledge of safety/content filtering for generated images
- Hands on work hillclimbing AI evaluations.
Compensation
-
Data Science 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.
-
Data Science 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:
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.
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Get Access To All JobsTips for Finding AI Engineer Jobs at Microsoft Jobs
Align your portfolio to Microsoft's AI stack
Microsoft's AI engineering roles frequently involve Azure OpenAI Service, PyTorch, and large-scale distributed training. Tailor your GitHub projects and resume to reflect experience with these tools before applying, as role-fit signals matter during initial screening.
Target teams with active LCA filings
Before you apply, search DOL's FLAG system for Microsoft's Labor Condition Applications filtered to AI and machine learning job titles. Active LCA filings signal which specific teams are currently hiring sponsored roles, letting you prioritize those positions.
Distinguish between H-1B and E-3 eligibility early
If you're an Australian citizen, clarify your E-3 eligibility before the offer stage. Microsoft sponsors both, but the filing process and timelines differ. Raising this with your recruiter early prevents delays when the offer comes through.
Use Migrate Mate to surface sponsorship-confirmed openings
Many Microsoft AI Engineer postings don't explicitly state visa sponsorship availability. Use Migrate Mate to filter for roles at Microsoft that have a confirmed sponsorship track record, so you're not guessing from a generic job description.
Prepare your specialty occupation documentation now
USCIS requires H-1B petitions to establish that an AI Engineer role qualifies as a specialty occupation. Gather your degree transcripts, any advanced coursework in machine learning or computer science, and publication or project records before your employer initiates filing.
Account for H-1B cap timing in your start date negotiation
If you're cap-subject, the earliest H-1B employment start date is October 1. When negotiating your offer, build this into your proposed start date to avoid gaps, especially if you're currently on OPT and approaching your authorization expiry.
AI Engineer at Microsoft jobs are hiring across the US. Find yours.
Find AI Engineer at Microsoft JobsFrequently Asked Questions
Does Microsoft sponsor H-1B visas for AI Engineers?
Yes, Microsoft sponsors H-1B visas for AI Engineer roles. The company files both cap-subject and cap-exempt petitions depending on the candidate's situation. If you're already on H-1B with another employer, Microsoft can file an H-1B transfer, which lets you start work as soon as USCIS receives the petition rather than waiting for approval.
How do I apply for AI Engineer jobs at Microsoft?
Applications go through Microsoft's careers portal, where AI Engineer roles are listed under the Engineering and Software job family. Filter by location and job title to find active openings. To identify roles where sponsorship is actively being offered, Migrate Mate surfaces Microsoft AI Engineer positions with a confirmed visa sponsorship track record, saving you from applying blind.
Which visa types does Microsoft commonly sponsor for AI Engineer roles?
Microsoft sponsors H-1B visas for the broadest pool of international AI Engineers. Australian citizens can pursue the E-3 visa, which has no lottery and a faster processing path. For candidates on employer-sponsored Green Card tracks, Microsoft supports EB-2 and EB-3 categories through PERM labor certification, typically initiated after a candidate has been in role for a defined period.
What qualifications does Microsoft expect for AI Engineer roles?
Most AI Engineer openings at Microsoft expect a bachelor's or master's degree in computer science, electrical engineering, or a closely related field, with hands-on experience in machine learning frameworks such as PyTorch or TensorFlow. Roles closer to foundation model work increasingly expect familiarity with distributed training, RLHF pipelines, or inference optimization. A strong portfolio demonstrating production-scale ML systems strengthens your application significantly.
How do I understand the visa filing timeline after receiving an offer from Microsoft?
After accepting an offer, Microsoft's immigration team typically engages an outside counsel to manage the petition. For H-1B transfers or E-3 cases, USCIS processing runs roughly three to six months standard or two to three weeks with premium processing. If you're cap-subject and the offer comes outside the April registration window, your start date will be October 1 of the following fiscal year.
See which AI Engineer at Microsoft employers are hiring and sponsoring visas right now.
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