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Senior Applied Scientist - Microsoft Word Copilot
必备技能
Python
TypeScript
JavaScript
C/C++
Natural Language Processing
Generative AI
Machine Learning
Software engineering
Mentoring
Overview
Come join Microsoft Word Copilot to work on state-of-the-art services, AI solutions and platforms and deliver the next generation of intelligent productivity experiences used by hundreds of millions of users daily! We are looking for a Senior Applied Scientist who can help us further grow our products, business, and culture!
At Microsoft Word Copilot team in Microsoft Development Center Serbia (MDCS), we have been focusing on reimagining and empowering Microsoft Word Office productivity through AI-powered user experiences and services built across core Microsoft Office applications. Microsoft Copilot combines the power of large language models (LLMs) with your organizational data, having native integration with Office apps to streamline your productivity: content generation, app navigation, comprehension and more. The team is relentlessly focused on making AI and tech work for people!
Applied Science team within Office Serbia is focused on end-to-end building and deploying state-of-the-art deep learning models for various AI applications across Microsoft Office suite of products. The team works with product and research teams around the globe to design, build, and evaluate LLM-based features, agentic systems, multimodal models, and deep learning solutions at scale. If you are passionate about applying cutting edge technology to positively impact the lives of millions of people, this is the job for you.
Responsibilities:
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Drive intelligent experiences, projects, and open-ended problems through their entire lifecycle from ideation through implementation, experimentation and finally to world-wide availability.
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Develop, adapt and deploy Generative AI and deep learning models in real-world product scenarios.
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Demonstrate rigor in key scientific procedures in AI based development process, including data, training, prompt engineering and evaluation methodologies.
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Define and implement robust evaluation frameworks and metrics, in partnership with product teams, to measure the quality of a wide range of AI features and inform decision-making and the design of AI-powered experiences.
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Lead experimentation through offline evaluation and A/B testing to measure user and business impact
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Collaborate with other research and engineering teams to adopt and advance state-of-the-art technologies.
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Follow strong engineering and documentation practices; participate actively in code reviews, bug/issue triage with the feature teams, and support well informed decisions towards business goals.
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Foster a healthy and inclusive team environment; provide technical leadership and mentorship to other applied scientists.
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Maintain, nurture and build relationships with international teams within Microsoft. Build strong cross-team partnerships and multiply impact across the team.
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Stay current with research trends and influence product and technical strategy. Qualifications
Qualifications-
BSc in Computer Science, Electrical Engineering, Mathematics, or related disciplines or equivalent industry experience.
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Proficiency with Python and experience with one or more other programming languages including, but not limited to Type Script, JavaScript, C/C++.
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Strong software engineering fundamentals, including coding, software design, problem solving, and data analysis skills.
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2+ years of experience in Natural Language Processing (NLP) and Generative AI.
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3+ years’ experience designing and shipping ML-powered systems across the product lifecycle.
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Experience with guiding or mentoring applied scientists or engineers.
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Ability to thrive in collaborative, fast-moving, and ambiguous environments.
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Demonstrated growth mindset and passion for AI innovation.
Preferred Qualifications:
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Deep experience in applied machine learning (e.g., NLP/LLMs, predictive analytics, computer vision, statistics).
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Experience developing evaluation frameworks for AI/LLM systems, including offline and online evaluations, human-in-the-loop setups, and metric design.
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Experience conducting applied research in industry settings.
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Master's Degree or Doctorate in Machine Learning, Computer Science, Electrical or Computer Engineering, Statistics or related field
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Strong written and verbal English communication skills.
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
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关于Microsoft

Microsoft
PublicMicrosoft Corporation is an American multinational technology conglomerate headquartered in Redmond, Washington.
10,001+
员工数
Redmond
总部位置
$3000B
企 业估值
评价
10条评价
4.4
10条评价
工作生活平衡
3.2
薪酬
4.1
企业文化
4.3
职业发展
3.8
管理层
4.0
82%
推荐率
优点
Cutting-edge technology and innovative projects
Great team culture and collaborative atmosphere
Excellent benefits and competitive compensation
缺点
Heavy workload and frequent overtime
High expectations and stressful environment
Bureaucratic processes can be slow
薪资范围
5,620个数据点
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
Mid/L4 · Applied Science
1份报告
$234,166
年薪总额
基本工资
$180,128
股票
-
奖金
-
$234,166
$234,166
面试评价
1条评价
难度
4.0
/ 5
时长
14-28周
体验
正面 0%
中性 0%
负面 100%
面试流程
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
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