Applied Scientist
@ Microsoft

Hybrid
$150,000
Hybrid
Full Time
Posted 10 hours ago

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Job Details

About the Applied Scientist Role

The M365 Core organization at Microsoft is seeking Mid Level and Senior Applied Scientist professionals. You will work to advance artificial intelligence, machine learning, and model optimization within Microsoft 365's core services.

Responsibilities

  • Conduct R&D to advance model training and evaluation.
  • Fine-tune large language models on tenant data.
  • Collaborate with engineers and researchers on deep learning and NLP.
  • Measure and analyze model performance using statistical methodologies.
  • Promote a culture of inclusion, respect, and accountability.

Qualifications

Possess a Bachelor's, Master's, or Doctorate in relevant fields, or equivalent experience. Candidates must have demonstrated expertise in training and fine tuning AI/ML models (preferably LLMs), productizing ML/AI components at internet scale, and proficiency in a programming language such as Python.

Preferred Qualifications

Experience in end-to-end problem solving, building Generative AI pipelines, and creating publications such as patents or academic papers.

Key skills/competency

  • machine learning
  • deep learning
  • LLM
  • NLP
  • model optimization
  • AI
  • predictive analytics
  • statistics
  • Python
  • research

How to Get Hired at Microsoft

🎯 Tips for Getting Hired

  • Research Microsoft culture: Understand mission, values, and innovations.
  • Customize resume: Emphasize AI, ML, and Python projects.
  • Tailor cover letter: Highlight role-specific skills and achievements.
  • Prepare for interviews: Practice technical and behavioral questions.

📝 Interview Preparation Advice

Technical Preparation

Review Python machine learning libraries.
Study deep learning frameworks usage.
Practice fine-tuning language models.
Analyze statistical performance metrics.

Behavioral Questions

Describe teamwork in high-pressure settings.
Explain conflict resolution examples.
Share innovation in problem-solving.
Discuss adaptability in agile projects.

Frequently Asked Questions