Research Intern - Artificial Intelligence Machine Learning 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.

The candidate will leverage external and internal data to identify talent pools, assess market feasibility, and uncover competitive trends. You will design and implement sourcing strategies that go beyond traditional methods—using intelligence to anticipate and track talent movement, research competitors and industry trends, and optimize our location strategies.

Required/minimum qualifications

• Bachelor's Degree AND 6+ years talent acquisition experience (e.g., recruiting, sourcing), HR experience, or industry experience related to role
  • OR equivalent experience.
• 4+ years of talent and market intelligence experience

Additional or preferred qualifications

• Bachelor's Degree AND 12+ years talent acquisition experience (e.g., recruiting, sourcing), HR experience, or industry experience related to role
  • OR Master's Degree AND 8+ years talent acquisition experience (e.g., recruiting, sourcing), HR experience, or industry experience related to role
  • OR equivalent experience.
• 4+ years of market research to map and track talent, key competitors, and industry trends.
• 4+ years of documenting and delivering actionable insights of market research to formulate a differential sourcing strategy.

• 10+ years of experience in Sales, Partner/Channel development, business development, alliance management in the technology industry
  • Experience articulating technology platform strategy and solutions with a great proficiency
  • Good candidate will be inclusive and collaborative, drive teamwork and cross-team alignment and will have strong relationship management and solution development skills
  • Strong executive presence including communication and presentation skills with a high degree of comfort to large and small audiences.
  • Strategic thinker who drives for impact. Strong candidates with problem solving mentality leveraging internal and/or external resources, conflict resolution, and follow through with partners.
  • Bachelor’s degree required; MBA desired.

• Sales Leadership

• Partner Success

• : Create strategic business objectives and partnership plans, coordinate partner prioritization and growth, ability to set clear goals/timelines for the business to achieve or exceed on revenue/metric targets and drive execution against agreed plans. Demonstrate the ability to make decisions in a fast-paced and rapidly changing environment.

• Focus on Performance Management with partners

is committed to advancing cutting-edge AI technologies that enable deeper understanding and interaction with people, objects, and environments in the 3D real world. Our research spans a diverse range of areas, including computer vision, generative AI, 3D perception, and robotic action learning, among others relevant to Embodied AI. By pushing the boundaries of these domains, we aim to develop innovative solutions that bridge the gap between the digital and physical worlds, empowering AI systems to perceive, comprehend, and navigate complex real-world scenarios.

Required Qualifications:

• Currently enrolled in a PhD program in Robotics, Machine Learning, Computer Science, or a related STEM field.
• Research experience inembodied AI, robotics, AI models, natural language, computer vision, demonstrated for example through research in a related PhD program and/or publications in conferences or scientific journals.
• Hands-on experience with Python and modern deep learning frameworks.
• Excellent problem-solving skills and the ability to work independently as part of a team.
• Strong communication skills and the ability to present complex ideas clearly.

Other Requirements:

• Ability to physically work from Microsoft Research Asia – Tokyo (Japan) for the duration of the internship.
• Must obtain permission from your academic advisor and commit to at least four months of internship.

Preferred/Additional Qualifications:

• Proven software engineering skills, evidenced by professional experience, internships, and impactful open-source contributions.
• Practical experience with handling data and robot learning, such as experience in Vision-Language-Action modelsor Hand Object Interactions.
• Familiarity with1)robot learning for robot hand manipulationor 2) hand pose estimation techniques or 3) reasoning techniques (Chain-of-Thought) used in LLM.

• Contribute to a high-impact research agenda within the context of a highly collaborative research culture alongside a team of experts in Embodied AI.
• Design and implement experiments to test new hypotheses and validate research findings.
• Communicate research findings to an interdisciplinary research team.
• Prepare technical papers, presentations, and open-source releases of research code.

At , we believe machine learning and artificial intelligence has the potential to transform scientific modelling and discovery crucial for solving the most pressing problems facing society including sustainable materials and discovery of new drugs.

Required:

• PhD or equivalent experience in Computer Science, Machine Learning, Applied Mathematics, Computational Biology, or related field.
• Strong software engineering in Python (packaging, testing, CI), with systems thinking for data‑intensive ML.
• Deep learning experience (PyTorch/JAX/TensorFlow) and solid foundations in linear algebra, probability, and statistics.
• Proven experience designing robust data pipelines for large‑scale ML (HPC or cloud).
• Ability to reason about learning signal and to assess information content of real‑world scientific datasets.
• Excellent collaboration and communication in interdisciplinary teams.

Preferred:

• Hands‑on cryo‑EM experience (e.g., map reconstruction, refinement, or pipeline tooling).
• CUDA or C++ for performance‑critical components; experience with mixed precision and memory‑efficient training.
• Experience integrating experimental data into ML models (e.g., constraints/priors from cryo‑EM, binding assays, spectroscopy).
• Familiarity with MD data, structure prediction systems, or protein design work-flows.
• Experience with cost‑optimization for data collection and cloud utilization; clear track record of building reliable, maintainable research software at scale.
• Experience with structural biology or molecular biology data/techniques (e.g., cryo‑EM, binding assays, spectroscopy, expression, sequencing)

• Data integration for structure & dynamics: Build ingestion/curation pipelines for structural/biophysical data (mmCIF/PDB, EM maps/particles, binding/biophysics, spectroscopy); implement map/volume preprocessing (e.g., resolution filtering, normalization) and alignment to model inputs/outputs.
• Cryo‑EM expertise: Operationalize end‑to‑end flows from raw image stacks/particles to 3D maps and model‑ready tensors; interoperate with community formats (e.g., EMDB/EMPIAR, mmCIF) and link to sequences/annotations.
• Signal & information content: Design dataset diagnostics (e.g., mutual‑information‑like measures, effective sample size, SNR proxies) to quantify what data teach the model; build active‑learning loops that maximize learning per euro of data collection time.
• Model‑aware data services: Implement scalable, versioned data services and feature stores that feed training/evaluation; design loaders/augmentations optimized for throughput and correctness (GPU‑aware).
• Training‑at‑scale engineering: Own distributed data pipelines and orchestration for large runs on Azure; profile and tune I/O, storage tiers, data locality, and caching; monitor cost, utilization, and failure modes.
• Quality, governance, and reproducibility: Codify schemas/ontologies, metadata contracts, unit/integration tests, and lineage; automate validation and data drift detection; maintain documentation and examples.
• Partner across disciplines: Work closely with ML researchers, structural biologists, and drug designers; translate experimental constraints into robust computational workflows; communicate clearly and proactively.

You will be responsible for the design, development, and execution of an exciting research agenda in collaboration with other machine learning, engineers, clinicians, social scientists, and designers at Health Futures. To learn more about this opportunity, please visit:

Qualifications

• PhD in Machine Learning, Computer Science or related fields or equivalent experience.

Required

• Relevant years of experience working on a multidisciplinary team working on AI research for real world impact.
  
• Hands-on experience with large scale deep learning models and libraries (e.g., PyTorch, TensorFlow).
  
• Strong software development skills.

Preferred

• Publications at top conferences and journals such as: NeurIPS, ICML, ICLR, MICCAI, Nature, CVPR, ICCV, EMNLP, ACL.
  
• Experience with medical domains such as radiology, digital pathology, genetics, immunology.
  
• Machine learning expertise in multi-modal learning, large language models (e.g., alignment), reinforcement learning and/or domain adaptation and data-efficient learning.

The ideal candidate will have a strong intellectual curiosity and passion to solve real-world problems in healthcare and multi-modal AI The responsibilities will include:

• Advance multi-modal medical AI, empowering internal and external partners to build and deploy state of the art medical imaging AI to make clinical work-flows faster and safer and improve patient outcomes.
• Collaborate on design, implementation and evaluation of multi-modal machine learning solutions which consider key clinical factors and responsible AI.
• Support the strategic planning of the team by providing engineering and research leadership.
• Engage with external and internal collaborators to drive real world impact.

As an
Industry Advisor for Defence and Intelligence, you will play a pivotal role in driving digital transformation and innovation across the Defense and Intelligence industry. Your mission is to engage with executive-level stakeholders to co-create strategies that unlock new revenue streams, optimise operations, and deliver hyper-personalised experiences through cutting-edge technologies.

You will bring deep domain expertise in the Japanese Defence Industry , with a strong understanding of industry-specific applications for AI and digital in the Defence ecosystem. Your insights will help shape transformation strategies that align with broader business goals and industry trends.

Qualifications

Required/Minimum Qualifications

• Bachelor's Degree in Computer Science, Information Technology, Engineering, Business or related field AND 10+ years customer-facing experience in the Defence Industry

• OR Master's Degree in Computer Science, Information Technology, Engineering, Business or related field AND 8+ years customer-facing experience in the Defence Industry

• OR equivalent experience.

Key Responsibilities

• Strategic Engagement : Act as a trusted advisor to C-level decision-makers, identifying innovation opportunities and aligning technology capabilities to industry-specific challenges.
• Digital Transformation Leadership : Guide customers through the adoption of AI, cloud, and data-driven solutions to modernise legacy systems, enable predictive operations, and accelerate time-to-market for new services.
• Sales Enablement : Lead industry-focused sales motions, support account planning, and contribute to pipeline growth through thought leadership and customer co-innovation.
• Ecosystem Collaboration : Partner with ISVs, SIs, and infrastructure providers to scale industry solutions across the WWPS landscape.
• Knowledge Sharing : Translate complex industry trends into actionable insights for internal teams, helping shape go-to-market strategies and solution development.

Planning & Engagement

• Acts as the industry expert in digital transformation account planning, driving engagement with internal/external stakeholders (e.g., Key Business Leaders, GSIs, ISVs).
• Provides thought leadership on global industry trends to activate and evangelize Microsoft strategies in local markets and key accounts.
• Leads relationship and stakeholder mapping to identify influential decision makers, accelerating account maturation and strategic alignment.
• Owns multi-horizon planning, creating segment-focused roadmaps based on business and technology priorities.
• Builds influential relationships with executive-level decision makers, positioning Microsoft as a strategic partner.
• Navigates complex environments to ensure alignment and execution of account roadmaps, regularly communicating as a thought leader.

Sales Execution

• Identifies solution opportunities and gaps based on customer needs and priorities.
• Advances high-impact, repeatable use cases and scenarios for reuse across customers and solution plays.
• Envisions new product scenarios and works with product teams to address white spaces.
• Accelerates solution plays with an industry narrative, leveraging expertise to drive innovative opportunities.
• Leads strategic discussions with board-level and senior executive stakeholders to design end states aligned with customer goals.
• Shapes strategy by providing long-term recommendations and building compelling business-value cases for Microsoft solutions.
• Recognized as a trusted advisor, guiding senior decision makers through consultative selling and strong financial business cases.

Collaboration & Partner Management

• Engages with Business Strategy Leads, Business Decision Makers, and Partner Development Managers to orchestrate customer opportunities.
• Collaborates with Industry Solutions Delivery, solution architects, and external stakeholders to design envisioned solutions.
• Drives go-to-market strategy and formal partnerships, articulating the case for developing solutions on Microsoft cloud.
• Shares consultative selling approaches and best practices, guiding account teams and prioritizing scalable opportunities.

Industry Expertise

• Completes required training and certifications, acting as a subject matter expert and thought leader.
• Shares industry depth, trends, and policy implications, providing recommendations and feedback across teams.
• Proactively seeks additional training to build career competencies and industry-specific expertise.