Security Research jobs at Microsoft in Taiwan, Taoyuan City

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.

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.

• Demonstrated technology-related sales or account management experience

• Bachelor's Degree in Information Technology

• Cybersecurity industry experience.Microsoft security portfolio knowledge preferred

• Demonstrated experience selling complex, cloud-based solutions to Enterprise customers.

• Proven sales and negotiation experience.

• Proven self-starter able to work towards delivery of goals as best practices are being developed

• Able to drive technical security conversations and conduct product/solution demonstrations.

• Solid understanding of security market and complete solutions

• Experience in managing channel sales
• Fluent spoken German and English

• You will engage in conversations with customers aligned to their industry and collaborate with account and partner team to drive and qualify new opportunities and build pipeline.
• You will leverage digital selling including digital signals to drive customer interests and identify new stakeholders at the customer.
• You will identify customer business and technology readiness, proactively builds external stakeholders' mapping, implements strategies to accelerate the closing of deals, contributes input on strategies to drive and close prioritized opportunities, coaches junior team members in deal plan execution, and implements close plans.
• You will accelerate opportunities from the Lead stage to closing the opportunity successfully in a strong seller to seller alignment with our key security partners.​
• You will apply role orchestration model and navigates the Microsoft organization to bring the best impact to the customer.​
• You will collaborate with Global Partner Solutions (GPS), identify new partners, develop joint proposals with partners and contribute to developing partner strategies.
• You will leverage and share competitor knowledge across solution areas as a subject matter expert to inform decisions on pursuit or withdrawal.
• You will lead conversations and set up events within Microsoft, mentors others and develop strategies for best practice sharing, initiate conversations with prospective customers/partners at events, act as a subject matter expert in one or more solution area(s).
• You will collaborate with the 'compete' SMEs internally to analyze competitor products, solutions, and/or services and implement strategies and drive the execution of projects, partners and collaborates with other teams on related deliverables, and leverages others in relevant work streams.

Minimum Qualifications:

• Bachelor's Degree in Statistics, Mathematics, Computer Science or related field.
• OR 3+ years experience in software development lifecycle, large-scale computing, modeling, cybersecurity, and/or anomaly detection.
• 3+ years of software development/research experience utilizing knowledge of security/threat landscape Practical Windows internals knowledge (other OS experience may count).
• 1+ years of experience with Reverse Engineering: familiar with debuggers, disassemblers, protocols, file formats.

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 background and Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred Qualifications:

• Master's Degree in Statistics, Mathematics, Computer Science or related field.
• OR 4+ years experience in software development lifecycle, large-scale computing, modeling, cyber-security, and/or anomaly detection.
• Offensive security research experience.
• Digital forensics skills Programming skills in C, C++, C# or willingness to learn Industry recognized author of security research papers, blogs, or books Low-level/security knowledge of other operating systems.

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 August 21, 2025.

As a Security Researcher II, you will:

• Research emerging attack vectors and techniques.
• Analyze detection and prevention gaps and understand root cause.
• Design and develop detection, prevention and disruption solutions to thwart advanced attacks.
• Synthesize in-field telemetry to judge the state of threat coverage and share insights.
• Identify trends, foresee landscape direction and propose enhancements to meet the needs.
• Collaborate across teams to address systemic security issues.
• Guide design of AI based solutions to tackle hard security problems.

ooking for amodernize their security architecture and posture.be at the forefront of innovation, working onprojects that

As aSolution Engineer (SE), you will play a pivotal role indriving securityacross every stage of the development lifecycleAs a trustedapplications and agentsinto their development workflows.improve their security,modernize their

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

• Drive technical sales with decision makers using demos andPoCsto influence solution design and enable production deployments.

• Lead hands-on engagements—hackathons, code-with sessions, and architecture workshops—to accelerate adoption of Microsoft’s developer tools and cloud platforms.

• Build trusted relationships with developers and platform leads, co-designing secure, scalable architecturesand solutions

• Resolve technical blockers and objections, collaborating with engineering to share insights and improve products.

• aintain

• Develop strategies and recommendations to improve the client's security posture,shapestechnicalwin plan andtailorsMicrosoft messaging toaudiencefor security opportunities. Enhances team capabilities for extended detection and response (XDR), zero trust and cloud security and develops differentiatedcompetestrategies for Microsoft Security for assigned customers.

• Represent Microsoft through thought leadership in developer communities and customer forums

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.