Applied AI Engineer Jobs at Microsoft with Visa Sponsorship
Microsoft builds Applied AI Engineer roles around production-scale AI systems, from foundation model integration to responsible AI tooling. The company has a well-established sponsorship process for engineering roles in this space, covering both nonimmigrant and immigrant visa pathways for qualified candidates.
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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.
See all 26+ Applied AI Engineer at Microsoft jobs
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Get Access To All JobsTips for Finding Applied AI Engineer Jobs at Microsoft Jobs
Frame your portfolio around deployed AI systems
Microsoft's Applied AI teams prioritize engineers who've shipped models into production, not just research prototypes. Document latency benchmarks, model evaluation pipelines, and real-world usage metrics before your interviews to show applied depth.
Target teams already using Azure AI services
Job listings for Applied AI Engineers at Microsoft often signal which internal platform they're building on. Roles tied to Azure OpenAI, Copilot, or Responsible AI tooling tend to have faster hiring cycles and clearer sponsorship precedent.
Clarify your visa category early in recruiting
Microsoft sponsors multiple nonimmigrant categories including H-1B, E-3 for Australians, and H-1B1 for Chilean and Singaporean nationals. Identifying your eligible category before your offer stage prevents delays when the recruiter initiates the sponsorship process.
Understand how PERM timing affects your career mobility
If Microsoft sponsors your Green Card through PERM, the DOL audit and prevailing wage determination process can take 18 months or longer. Applied AI engineers from high-backlog countries should factor this into promotion and internal transfer decisions early.
Use Migrate Mate to find open Applied AI Engineer roles at Microsoft
Microsoft's sponsorship-eligible openings are spread across multiple teams and geographies. Migrate Mate filters specifically for visa-sponsored positions, so you're only spending time on roles where sponsorship is confirmed rather than assumed.
Prepare for technical interviews that test AI system design
Applied AI Engineer interviews at Microsoft typically include a system design round focused on scalable ML infrastructure. Practicing retrieval-augmented generation architectures, fine-tuning workflows, and responsible AI evaluation frameworks gives you a concrete edge over candidates with only academic backgrounds.
Applied AI Engineer at Microsoft jobs are hiring across the US. Find yours.
Find Applied AI Engineer at Microsoft JobsFrequently Asked Questions
Does Microsoft sponsor H-1B visas for Applied AI Engineers?
Yes, Microsoft sponsors H-1B visas for Applied AI Engineer roles. The company is one of the most active H-1B sponsors in the technology sector and has established legal and HR infrastructure to support the full petition process, including the I-129 filing, LCA certification through DOL, and premium processing when timelines require it.
How do I apply for Applied AI Engineer jobs at Microsoft?
You can apply directly through Microsoft's careers portal, but filtering for visa-eligible openings manually is time-consuming. Migrate Mate surfaces Applied AI Engineer roles at Microsoft where sponsorship is confirmed, so you can apply directly to relevant listings without sifting through roles that don't support your visa situation.
Which visa types does Microsoft commonly sponsor for Applied AI Engineer roles?
Microsoft sponsors H-1B, E-3, and H-1B1 visas for nonimmigrant work authorization, covering Australian, Chilean, and Singaporean nationals alongside the general H-1B pool. For permanent residence, the company typically supports EB-2 or EB-3 Green Card pathways through the PERM labor certification process once an engineer has been in role for a qualifying period.
What qualifications does Microsoft expect for Applied AI Engineer positions?
Most Applied AI Engineer roles at Microsoft require a bachelor's or master's degree in computer science, machine learning, or a closely related field. Beyond the degree, interviewers focus heavily on production AI experience, specifically deploying and maintaining large language models or multimodal systems, contributing to model evaluation frameworks, and working within responsible AI guidelines at scale.
How do I plan my timeline if Microsoft is sponsoring my H-1B?
H-1B cap-subject petitions are filed in April for an October 1 start date, so your offer and LCA certification through DOL need to be in place before the registration window opens in March. If you're already on OPT or STEM OPT, you can begin work before October 1 under the cap-gap rule while your petition is pending with USCIS.
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