Principal Software Engineering Manager jobs at Microsoft in Taiwan, Taoyuan City

As a Software Engineering PhD Intern, you will work with teammates to solve problems and build innovative software solutions. You will apply your passion for customers and product quality as you provide technical guidance to Technical Program Managers and Product Managers. You will learn and adopt relevant new technologies, tools, methods, and processes to leverage in your solutions. This opportunity will enable you to advance your career by designing, developing, and testing next-generation software that will empower every person and organization on the planet to achieve more.

Required Qualifications

• Pursuing a PhD in Computer Science, Engineering, or related field during the academic term immediately before the internship.

• Must have at least 1 semester/term remaining following the completion of the internship.

• At least one year of programming experience in an object-oriented language.

Preferred Qualifications

• Ability to demonstrate an understanding of computer science fundamentals, including data structures and algorithms.
• Academic/research experience with distributed systems, network architecture, operating systems, and/or related topics.

The base pay range for this internship is USD $5610.00 - $11010.00 per month. 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 $7270.00 - $12030.00 per month.

• Applies engineering principles to solve complex problems through sound and creative engineering.

• Works with appropriate stakeholders to determine user requirements for a feature.

• Quickly learns new engineering methods and incorporates them into work processes.

• Seeks feedback and applies internal or industry best practices to improve technical solutions.

• Demonstrates skill in time management and completing software projects in a cooperative team environment.

• Reviews current developments and proactively seeks new knowledge that will improve the availability, reliability, efficiency, observability, and performance of products while also driving consistency in monitoring and operations at scale.

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

Agility: Ability to think, understand, and process information quickly.

Algorithm Design and Implementation: The ability to design, analyze, implement, optimize, profile and experimentally evaluate computer algorithms. Includes knowledge of practical applications of algorithms in software engineering.

Computer Science: The ability to apply computer science principles (e.g., data structures, algorithms, run-times), statistics and computer architecture to implement, adapt, or apply concepts when programming.

Detail Oriented: The ability to attend to and verify the accuracy and completeness of detailed information in documents, on the computer, and/or in other work products. This includes being able to code, file, compile, transcribe, classify, and/or track details from a variety of different sources/problems/issues.

English Language Proficiency: The ability to speak and understand English when giving instructions and directions, and when talking with colleagues, managers, and others for work matters.

Oral Communication: The ability to make a verbal message understood and to receive/understand messages during in-person or remote (e.g., telephone) interactions.

Problem Solving: The ability to identify problems and review related information to develop and evaluate options and implement solutions.

Software Development: Knowledge of the software development process, including conception, specification, design, programming, documentation, testing, and bug fixing to create and maintain applications, frameworks, or other software components.

Writes Code: The ability to write clear and efficient code in one or more relevant computer programming languages (e.g., Java, C/C++, Python, JavaScript) to develop computer programs that solve a business problem.

Written Communication: The ability to prepare clear, accurate, and understandable written text, and follow the basic rules of spelling, grammar, and punctuation. This may include memos, emails, proposals, reports, and professional or general correspondence.

Required Qualifications:

• Bachelor's Degree in Computer Science or related technical field AND 5+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience.

Other Requirements

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:

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

Preferred Qualifications:

• Master's Degree in Computer Science or related technical field AND 5+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR 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.

• Coding: Creates and implements code for a product, service, or feature, reusing code as applicable. Writes and learns to create code that is extensible and maintainable. Considers diagnosability, reliability, and maintainability with few defects, and understands when the code is ready to be shared and delivered. Applies coding patterns and best practices to write code. Supports efforts to apply debugging tools and examines logs, telemetry, and other methods to verify assumptions proactively before issues occur and reactively as issues occur for product features. Conducts retrospective debugging of solutions to identify root causes of problems. Reviews code of a product feature to assure it meets the team's and Microsoft's quality standards, is reliable and accurate and is appropriate for the scale of the product feature. Applies feedback to current and future iterations. Participates in code reviews to ensure coding standards are followed. Considers diagnosability, reliability, and maintainability when reviewing code and understands when code is ready to be shared or delivered.
• Design: Creates a clear and articulated plan for testing and assuring quality of solutions, and defines success for outcomes of tests (e.g., unit tests). Adds new tests, removes antiquated tests, and aggregates tests to improve tests in the feature area. Helps to drive efforts for augmenting test cases and ensures that the solution area has good test coverage. Helps to integrate automation features when planning for testing.
• Engineering Excellence: Builds knowledge, shares new ideas, and shares pinpoints of engineering tool gaps to improve software developer tools to support other programs, tools, and applications to create, debug, and maintain code for complex product features. Uses open source when possible. Develops higher-level awareness of other kinds of tools outside areas of expertise. Helps to identify internal tools and creates tools that will be useful for creating the product, determining if methods are still applicable for the current solution. Contributes to the development of automation within production and deployment of a complex product feature. Runs code in simulated, or other non-production environments to confirm functionality and error-free runtime for products with little to no oversight.
• Implement: Conducts and creates experimentation to determine the effectiveness of changes for prototyping and testing features, and applies findings back into development. Reviews work items to deepen knowledge of product features in partnership with appropriate stakeholders (e.g., project managers) and executes project plans, release plans, and work items. Contributes to efforts to break down larger work items into smaller work items and provides estimation. Escalates any issues that would cause a delay.
• Reliability and Supportability: Acts as a Designated Responsible Individual (DRI) working on call to monitor system/product feature/service for degradation, downtime, or interruptions. Alerts stakeholders as to the status and gains approval to restore system/product/service for simple problems. Responds within Service Level Agreement (SLA) timeframe. Escalates issues to appropriate owners. Identifies areas to efforts to integrate instrumentation for gathering telemetry data on system behavior such as performance, reliability, availability, usage, and safety mechanisms. Contributes to sustaining feedback loops from telemetry resulting in subsequent designs. Helps to create outputs of telemetry such as notifications or dashboards.
• Understand User Requirements: Works with appropriate stakeholders (e.g., project manager, technical lead) to determine user requirements for a set of features. Begins to leverage a variety of feedback channels to incorporate insights into future designs or solution fixes. Incorporates appropriate continuous feedback loops measuring customer value, usage patterns, and other actionable metrics of value.

Clearance requirement

• Ability to get clearance for government related technology engagement

Required/minimum qualifications

• Master's or Bachelor' Degree in Computer Science, business, or related field AND 3+ years customer success, solution delivery, practice management, customer-facing consulting, or portfolio management experience
• 3+ years of working experience in public safety and defense or public sector

Required Qualifications:

• Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience.

Other Requirements:

• 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 Cloud Background Check upon hire/transfer and every two years thereafter.

Preferred 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 Master's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience.

• Contribute to developing a holistic resource lifecycle management system.
• Focus on securing, validating, and provisioning the Azure platform.
• Play a role in supporting the fastest growing cloud platform in the market.
• Gain visibility into the internals of Azure core services
• Learn how services bootstrap and scale.
• Opportunity to own a high-impact area of the platform.
• Directly influence areas with million-dollar business impact.

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.