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Microsoft Applied Scientist Taiwan, Taoyuan City 405953182
25.09.2025
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If yes, you'll love this opportunity.
Required Qualifications:
- Bachelor's Degree in Computer Science, Statistics, Econometrics, Electrical or Computer Engineering, or related field AND relevant internship experience (e.g., statistics, predictive analytics, research)
- OR Master's Degree in Computer Science, Statistics, Econometrics, Electrical or Computer Engineering, or related field
- OR equivalent experience.
- Conduct applied science experiments, create and validate metrics, work with ML pipeline and modeling algorithm in the area of Large Language Models, Natural Language Processing, Information Retrieval, and Machine Learning.
- Develop and deploy conversational and language understanding models at scale.
Preferred Qualifications:
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ 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
- OR equivalent experience.
- Experience with coding in Python TypeScript or any strongly typed equivalent and production system machine learning
- Experience with commercial product development with strong focus on user experiences.
- Following and advancing best practices for Responsible AI and Privacy Preserving Machine Learning.
- Collaborate closely with Microsoft Research, Microsoft AI groups, Microsoft Azure, AI platform teams, and product teams to create the next generation of AI innovation in our products and services.
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 September 27, 2025.
Responsibilities
- Design, implement, validate, and ship AI-powered features end-to-end for Microsoft Teams across desktop, web, and mobile clients.
- Collaborate with Program Managers, Designers, and Researchers to define product requirements, timelines, and measurable success criteria.
- Maintain and improve system performance, reliability, latency, and scalability of AI-powered features in production.
- Participate in writing code, code reviews, debugging, telemetry reviews, and continuous delivery processes.
- Champion a culture of scientific rigor, ethical AI, and innovation across the team.
- Communicate scientific findings and technical designs clearly to product and engineering leadership.
- Drive exploration of hybrid AI experiences (cloud + edge + LLM) for responsiveness, privacy, and enterprise value.
- Experience prompt tuning, fine tuning and RAG system development.
- Experience with Evaluation, A/B testing, Experimentation.
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