Applied Scientist
Technology, Data & Digital · Data, AI & Analytics · Data Science · Machine Learning · Artificial Intelligence
In short
Responsibilities
- Own end-to-end applied research and engineering to improve web data quality, scale, and model readiness for Search, grounding, and LLM training.
- Develop and apply state-of-the-art machine learning, LLM, statistical, and data mining techniques to solve complex web-scale problems and advance platform capabilities.
- Analyze large-scale web data, formulate hypotheses, and design rigorous experiments that produce trustworthy, actionable insights and measurable impact.
- Apply LLMs and prompt engineering to score, classify, label, and evaluate data, enabling scalable model training, evaluation, and continuous improvement.
- Translate complex technical problems and research findings into product decisions, technical strategies, and engineering roadmaps in partnership with stakeholders.
- Collaborate across Microsoft AI, document and share learnings, and establish best practices for scalable, responsible, and privacy-conscious AI and data solutions.
Requirements
- 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 AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research).
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field.
- OR equivalent experience.
Desired Qualifications
- 1+ years of experience contributing to research publications, patents, or peer-reviewed academic papers.
- 1+ years of experience in product development in machine learning and related areas.
- Hands-on experience developing algorithms and models using deep learning frameworks such as TensorFlow and PyTorch.
- Hands-on experience with large language models (LLMs), such as GPT, BERT, or similar architectures, with an understanding of their capabilities and limitations.
- Knowledge of natural language processing (NLP), including tokenization, semantic understanding, representation learning, classification, and text generation.
- Understanding of modern machine learning and deep learning techniques, with hands-on experience using architectures such as Transformers/Attention, DNNs, CNNs, or RNNs and frameworks such as PyTorch, TensorFlow, or Keras.
- Algorithmic, statistical, and analytical skills, with demonstrated ability to apply advanced techniques to complex, real-world problems.
- Ability to translate technical vision into experimentation, system design, implementation, and measurable results, working both independently and collaboratively across teams.
- Experience with large-scale or distributed data processing, high-performance computing, stream processing, or SCOPE is preferred.
Benefits
- Potential eligibility for benefits and other compensation.
- Access to additional benefits and pay information via provided link.
Skills
About Microsoft
Empowering every person and organization on the planet to achieve more
Every company has a mission. What's ours? To empower every person and every organization to achieve more. We believe technology can and should be a force for good and that meaningful innovation contributes to a brighter world in the future and today. Our culture doesn’t just encourage curiosity; it embraces it. Each day we make progress together by showing up as our authentic selves. We show up with a learn-it-all mentality. We show up cheering on others, knowing their success doesn't diminish our own. We show up every day open to learning our own biases, changing our behavior, and inviting…
Company
MicrosoftJob Posted
4 days ago
Employment Type
Full Time
Work mode
Hybrid
Salary
US$102,100–219,200 · Negotiable
Hours per week
32
Experience Level
Mid-Senior
Locations
United States
Qualification
Applicants
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