Principal Applied Scientist- Feeds Ai jobs at Microsoft in Taiwan, Taoyuan City

and multi-disciplinary group of scientists,

Principal Data & Applied Scienwork ongroundbreaking andhigh-impact projects at the intersection of AI and software engineering. In this role, you will drive the development and application of advanced data science techniques—especially those involving LLMs—to real-world developer workflows.. You will have the opportunity to design and lead experiments, build and evaluatemodels (including RAG pipelinesand evaluation frameworks), andinsights into scalable product features. Most importantly,play a key role in bridging

Required/Minimum Qualifications:

• degree in Computer Science, Engineering, Mathematics, Statistics

• +yearsexperiencewith strongproficiencyinPython, machine learning frameworks,and experience developing and deploying generative AI or machine learning models into production. (Experience withadditionalprogramming languages is a plus but notrequired

Preferred Qualifications

• or PhD degree in Computer Science, Statistics, or related fields (undergraduates with significantappropriate experiencewill be considered).

• Strong professional experience in statistics, machine learning, including deep learning, NLP, econometrics.

• Experience in building cloud-scale systems and experience working with open-source stacks for data processing and data science is desirable.

• Experience with LLMs in natural language, AI for code or related fields

• Excellent communication skills, ability to present andwritereports, strongteamworkand collaboration skills.

• Experience in productizing AI and collaborating with multidisciplinary teams.

• researchand productization ofstate-of-the-art in AI for Software Engineering

• Build and manage large-scale AI experiments and models.

• Drive experimentation through A/B testing and offline validation to evaluate model performance.

• and geographieswith product teamsinMicrosoft and Github

• Stay up to date with the research literature and product advances in AI for software engineering

• Collaborate with world renowned experts in programming tools and developer tools to integrate AI across software development stack for Copilot

• Lead others by exemplifying growth mindset, inclusiveness, teamwork, and customer obsession

Minimum Experience

• 5+ years technical pre-sales or technical consulting experience AND Bachelor's Degree in Computer Science, Information Technology Additional

  • or preferred qualifications 4+ years experience with cloud and hybrid

  • or on premises infrastructures, architecture designs, migrations, industry standards, and/or technology management Certification in relevant technologies or disciplines (Azure Architect and Development exams, Cloud Platform Technologies, Architecture).

• Drive technical sales conversations with business and technical decision makers, using demos and proof-of-concepts to shape solution design and accelerate production deployments.
• Lead hands-on engagements such as hackathons, code-with sessions, and architecture workshops to fast-track adoption of Microsoft developer tools and cloud platforms.
• Build trusted relationships with developers and platform leaders, co-designing secure, scalable, and innovative architectures.
• Resolve technical blockers and objections, working closely with engineering teams to provide feedback and influence product improvements.
• Develop and maintain expertise in AI Foundry and AI application architecture, including Agentic AI frameworks, Semantic Kernel, Foundry SDK, and Responsible AI.
• Grow skills in cloud-native development, including APIs, containerization, microservices, event-driven systems, and programming in Python, Java, or .NET.
• Expand knowledge in AI management and security, including GenAI Ops, Sentinel, orchestration, and monitoring.
• Represent Microsoft as a thought leader in developer communities and customer forums.

Required/Minimum Qualifications:

• Bachelor’s degree in computer science, Information Technology, Engineering, or a related field AND 6+ years of experience in cloud/infrastructure technologies, software development/support, analytics/BI system development, or artificial intelligence (AI).

• Deep understanding of Cloud Infrastructure, Cloud Native solutions, containerization, and Dev sec ops.

• Familiarity with at least one development language (e.g., Python, Java, Go, C#, JavaScript, Scala).

• Problem Solving. Ability to solve customer problems through cloud technologies required

• 6+ years of experience in customer-facing IT project delivery.

Additional or Preferred Qualifications:

• Master’s degree in computer science, Information Technology, Engineering, or a related field AND 6+ years of experience in cloud/infrastructure technologies, software development/support, analytics/BI system development, or artificial intelligence (AI).

• Proficiency in multiple development languages (e.g., Python, Java, Go, C#, JavaScript, Scala).

• 8+ years of experience in customer-facing IT project delivery.

• 8+ years of experience leading technical projects.

• Technical Certification in Cloud (e.g., Azure, Amazon Web Services, Google Cloud, Alibaba Cloud, Tencent Cloud, security certifications).

Essential Skills:

• OpenAI/AI, Llama, Deepseek, Copilot including Github Copilot and Studio, and Cognitive services
• Microservices and containerization with Azure Kubernetes Services
• Advanced Analytics (Azure Synapse, Databricks, visualization tools such as PowerBI, Tableau, QuickBI)
• NoSQL Databases including OSS (Cassandra, Mongo, HBase, etc.), Cosmos DB

• Understand customers’ overall data estate, IT and business priorities and success measures to design implementation AI based architectures and solutions.

• Consumption (Cloud & Support) growth - Develop opportunities to drive Customer Success business results & help Customers get value from their Microsoft investments.

• Apply technical knowledge to architect solutions that meet business and IT needs, be advisor for customer’s Azure AI Platform strategy, applications modernization through microservices on Azure Kubernetes services, AA/AI roadmaps, and ensure long term technical viability of new deployments, infusing key analytics and AI technologies where appropriate (e.g. Azure ML, Azure AI Services including AI Search, Azure OpenAI, Copilot including Github Copilot and Studio, Cognitive Services, Spark, Data Lake, Azure Synapse, etc.)

• Ensure that solution exhibits high levels of performance, security, scalability, maintainability, appropriate reusability and reliability upon deployment.

• Be a Voice of Customer to share insights and best practices, connect with Engineering team to remove key blockers. Deliver according to MS best practices & using repeatable Intellectual Property (IP) and Value Based Delivery (VBD).

• Assess the Customers' knowledge of Azure platform and overall cloud readiness to support customers through a structured learning plan and ensure its delivery through partners.

• Collaborate with other Solution Engineers and other Cloud Solution Architects in developing complex end-to-end Enterprise solutions on Microsoft Azure platform.

• Maintain technical skills and knowledge, keeping up to date with market trends and competitive insights; collaborate and share with the technical community while educate customers on Azure platform.

• Be an Azure Platform evangelist with customers, partners and external communities.

Required Qualifications

• Master's Degree in Computer Science, Information Technology, or related field AND 4+ years technical pre-sales or technical consulting experience OR Bachelor's Degree in Computer Science, Information Technology, or related field AND 6+ years technical pre-sales or technical consulting experience OR 7+ years technical pre-sales or technical consulting experience OR equivalent experience.

Preferred Qualifications

• 10+ years technical pre-sales, technical consulting, or technology delivery, or related experience OR equivalent experience.
• 8+ years experience with cloud and hybrid, or on premises infrastructures, architecture designs, migrations, industry standards, and/or technology management.
• Certification in relevant technologies or disciplines (e.g., Office 365, Power BI, Azure Architect and Development exams, Cloud Platform Technologies, Information Security, Architecture).

Solution Design and Proof

Adapts and extends architecture patterns to accommodate complex customer requirements and drive integration solutions for industry flavor. Delivers assets that can be leveraged by others in the business.

The Security Models Training team builds and operates the large-scale AI training and adaptation engines that power Microsoft Security products, turning cutting-edge research into dependable, production-ready capabilities. As a, you will lead end-to-end model development for security scenarios, including privacy-aware data curation, continual pretraining, task-focused fine-tuning, reinforcement learning, and rigorous evaluation. You will drive training efficiency on distributed GPU systems, deepen model reasoning and tool-use skills, and embed responsible AI and compliance into every stage of the workflow. The role is hands-on and impact-focused, partnering closely with engineering and product to translate innovations into shipped experiences, designing objective benchmarks and quality gates, and mentoring scientists and engineers to scale results across globally distributed teams. You will combine strong coding and experimentation with a systems mindset to accelerate iteration cycles, improve throughput and reliability, and help shape the next generation of secure, trustworthy AI for our customers.

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)
  • OR Master's Degree in 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.
• 3+ years experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
• Proven track record training and shipping large language models or multimodal models for production scenarios, including continual pretraining and task specific adaptation.
• Proficiency in Python and PyTorch, with hands-on experience building and debugging large-scale training jobs.

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

Microsoft Cloud Background Check:
- This position will be required to pass the Microsoft background and Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred Qualifications:

• Security domain experience in one or more areas: security operations, threat intelligence, malware analysis, vulnerability and posture management, anomaly detection, phishing and fraud detection, or cloud identity and access.
• Experience with distributed training and scaling techniques, for example DeepSpeed, FSDP, ZeRO, model and pipeline parallelism, mixed precision, and profiling.
• Experience with privacy preserving ML including differential privacy concepts, privacy risk assessment, and utility measurement on privatized data.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:Microsoft will accept applications for the role until October 21, 2025.

• Lead the full modeling lifecycle for security scenarios, from data ingestion and curation to training, evaluation, deployment, and monitoring.
• Architect and optimize large-scale distributed training on GPU clusters, improving throughput, reliability, and cost efficiency.
• Design and implement privacy-preserving data workflows, including anonymization, templating, synthetic augmentation, and quantitative utility measurement.
• Develop and maintain fine-tuning and adaptation recipes for transformer models, including parameter-efficient methods and reinforcement learning from human or synthetic feedback.
• Establish objective benchmarks, metrics, and automated gates for accuracy, robustness, safety, and performance, enabling repeatable model shipping.
• Collaborate with engineering and product teams to productionize models, harden pipelines, and meet service-level objectives for latency, throughput, and availability.
• Mentor applied scientists and engineers, promote strong documentation and experiment hygiene, and foster a culture of rapid iteration grounded in responsible AI principles.
• Contribute to thought leadership by staying current with the latest AI advances and translating promising techniques into practical, measurable impact.

? The Business and Industry Solutions (BIS) team is looking for a Senior Applied Scientist to drive innovation at the intersection of AI, experimentation, and enterprise systems. In this role, you will design and evaluate autonomous agents that deliver measurable improvements in accuracy, latency, and cost-efficiency.lead rapid experimentation cycles, develop robust evaluation frameworks, and apply advanced techniques like reinforcement learning to enable multi-step reasoning and decision-making.collaborate across engineering, product, and partner teams to ensure agents are performant, secure, reliable, and extensible—empowering customers and partners to build on our platform. This is your opportunity to influence the next generation of AI-native business applications and deliver real-world impact at scale.

in natural language processing (NLP), witha strong foundationin large language model (LLM) development, evaluation, and fine-tuning. They should have hands-on experience in applying advanced fine-tuning techniques—including instruction tuning, reinforcement learning from human feedback (RLHF), and tool-augmented generation—to build agents capable of multi-step reasoning and decision-making. Familiarity with prompt/context engineering, context-aware orchestration, and integrating LLMs with external tools and APIs is essential. The candidate should be comfortable working in a fast-paced, experimentation-driven environment,both offline and online evaluation methods to iterate rapidly andagent behavior. A deep understanding of the challenges and opportunities in building AI-native enterprise applications will be key to success in this role.

Qualifications

• Bachelor's Degree in Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research)

• OR Master's Degree in Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)

• OR Doctorate in Computer Science, Electrical or Computer Engineering, or related field AND 1+ years related experience (e.g., statistics, predictive analytics, research)

• OR equivalent experience.
• 1+ years of experience withgenerativeAIOR LLM/ML

Preferred Qualifications:

• Experience withMLOpsWorkflows, including CI/CD, monitoring, and retraining pipelines

• Familiarity with modernLLMOpsframeworks (e.g.,LangChain,PromptFlow

• 3+ years of experience publishing in peer-reviewed venues or filing patents.

• Experience presenting at conferences or industry events

• 3+ years of experience conducting research in academic or industry settings
• 1+ year of experience developing and deploying live production systems

• 1+ years of experience working with Generative AI models and ML stacks
• Experience across the product lifecycle from ideation to shipping

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

• requiredto pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

• by executing high‑leverage data science and analytics initiatives within a product area or feature team, ensuring measurable improvements to user and business outcomes.

• Lead the design and implementationof advanced model fine‑tuning pipelines, including Reinforcement Learning from Human Feedback (RLHF), to align AI system behavior with user intent and improve performance in real‑world scenarios.

• Own complex, end‑to‑end projectsthat combine technical depth with cross‑functional collaboration, influencing feature direction and prioritization rather than broad organizational investment decisions.

• Foster alignment and trustacross partner teams through clear, actionable communication and collaborative problem‑solving.

• Develop and maintainrobust measurement systems, experimentation frameworks, and causal inference methodologies tailored to dynamic AI systems and enterprise‑scale environments.

• Mentor and supportpeers by sharing best practices, reviewing designs, and contributing to a collaborative, high‑performance team culture.

• Leverage AI tostreamline workflows and enhance team productivity through intelligent automation and innovation.