Microsoft Principal Applied AI Engineer 

Taiwan, Taoyuan City 

963668678

is responsible forthe Microsoft Dynamics 365 suite of products, Microsoft Copilot Studio, Power Apps, Power Automate, Dataverse, AI Builder, Microsoft Industry Solution and more. Microsoft is considered one of the leaders in Software as a Service in the world of business applications and this organization is at the heart of how business applications are designed and delivered.

organization at Microsoft is among the most thrilling to be a part of. BIC Agent Cloud products herald a new era of business applications that are data-initiated, AI-driven, built for collaboration, and simplify business problem-solving with low-code/no-code platforms. Our teamis responsible forand the Power Platform suite of low-code tools. We are at the vanguard of digital transformation, enabling organizations to revolutionize the creation of Copilots throughAI solutions and product offerings. This new productivity erathe power of data, AI, and productivity tools to deliver unmatched experiences across all channels.

a highly accomplishedPrincipal Appliedwith deepin large language models (including both text and multimodal systemsreinforcement learning, agentic AI architectures, and large-scale model training and inference optimization. This is a senior individual contributor role for a thought leader who brings togetherresearch excellence and strong applied instincts. You willat the frontier of AI science and product innovation, driving the design and deployment of next-generation AI systems at. You will need to design and build systems that allow LLMs to reason overlarge amountsof data as well aslighter weight models in place for specific scenarios for specific scenarios. We are looking for an individual who has the proven capability of working with research teams and partnering with them to deliver joint solutions.This can range from working togetherfine-tuned models tocoming up withways to build custom LLMs for specific product needs.

We are excited to hear from candidates who are passionate about making a significant impact on how people interact with their computers, and who are excited about the opportunity to be at the forefront of growing new business for Microsoft. This is a rare chance to be part of atechnology that is poised to revolutionize productivity and innovation.

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

Required Qualifications

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)

• master’s degreein Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)

• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)

• OR equivalent experience.

• years’ experiencewith transformer-based models (e.g., GPT, Llama).

• years’ experiencein coding and design, specifically in the development of AI models for scaled production services.

• years’ experiencein shipping applied research to production, highlightinga track recordof combining coding skills with advancedexpertisein AI model development.

Other Requirements

to meet Microsoft, customer and/or government security screening requirementsfor this role. These requirements include, but are not limited to the following specialized security screenings:

• This position will berequiredto pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred/Additional Qualifications

• Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 10+ years related experience (e.g., statistics, predictive analytics, research) or publication record in the areas of Large Language Models, Machine Learning, or Natural Language Processing.

• years’ experienceconducting research as part of a research program (in academic or industry settings).

• years’ experiencein coding and design, specifically in the development of AI models for scaled production services.

• years’ experiencein shipping applied research to production, highlightinga track recordof combining coding skills with advancedexpertisein AI model development.

• expertisein one or more of the following: supervised learning, deep learning, natural language processing, reinforcement learning, computer vision, time series forecasting, or causal inference.

• 6+ years of experience programming with C# is preferred

• Relevant experience in Applications of Foundation Models, Domain Adaptation of Foundation Models (e.g.fine-tuning LLMs/SLMs) orVision, Audio, and Multimodal Foundation Models or agentic Systems or PromptTuning orNatural Language Processing or Human-AI Interaction

• 6+ years of experiencedemonstratingproblem solving and data analysis skills, withexpertisein developing or applying predictive analytics, statistical modelling, data mining, or machine learning algorithms.

• 6+ years of experiencedemonstratingleadership skills to influence others, with the ability to understand team dynamics,retain, attract, and develop team members.

• 6+ years of experience demonstratingagrowthmindset, customer obsession, and Inclusion.

• 6+ years of experiece Demonstrated passion for product impact, includingstate-of-the-arttools, technologies, and methods being used in the research community and product groups.

Applied Sciences IC6 - The typical base pay range for this role across the U.S. is USD $163,000 - $296,400 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 $220,800 - $331,200 per year.

• Lead the design and development of advanced AI models and agentic systems for real-world applications.

• and drive end-to-end model training, including data pipeline design, distributed training optimization, and performance evaluation.

• Stay up to date with the latest advancements in LLM, NLP, deep learning,searchand AI research.

• Research and develop an understanding of thestate-of-the-arttools, technologies, and methodsbeing usedin the research community and product groups.Drive innovation by staying current with the latest research, technologies, and best practices in AI/ML, and Translate research breakthroughs into production-ready algorithms, contributing to core capabilities such as search, planning, and long-term memory.

• pipelinesand provide support for in production AI Models/Agents

• Collaborate with stakeholders to define project goals, success criteria, and deliverables.Leadend-to-end lifecycle of machine learning models, from prototyping and implementation to evaluation, deployment, and monitoring.

• fostera collaborative and innovative work environment.

• theteam'sstrategic vision, contribute to the organization’s scientific direction and align it with the overall companyobjectives,influencing roadmaps and long-term vision.

• Conduct applied science experiments,createandvalidatemetrics, develop ML pipeline and modeling algorithmin the area ofLarge Language Models, Natural Language Processing, Information Retrieval, and Machine Learning.

• Conduct experiments to evaluate model performance (including Large Language Models), troubleshoot issues, and iterate improvements.

• and deploy conversational and language understanding models atscale.

• Following and advancing best practices for Responsible AI and Privacy Preserving Machine Learning.

• Drive thought leadership, architecture for high scale, high throughput, low latency inferencing.

• Drive AI projects through their entire life cycle from idea creation through applied research, implementation, experimentation and finally to worldwide availability.

• Be involved in the onboarding process for new team members, providing guidance and support as they join the team.

• Embody our,