Principal Data Scientist – Deepfake Detection
@ Microsoft

Hybrid
$274,800
Hybrid
Full Time
Posted 23 hours ago

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Job Details

Overview

Microsoft Security is dedicated to creating a safer digital world. As a Principal Data Scientist – Deepfake Detection, you will work on developing, prototyping, and implementing solutions focused on detecting deepfakes and social engineering threats in audio/video mediums.

Key Responsibilities

  • Collaborate with partner teams to safeguard enterprise customers.
  • Drive research and experimentation on synthetic A/V detection.
  • Develop evaluation protocols and benchmark detection methods.
  • Implement and support production ML models and heuristics.
  • Participate in on-call rotation and incident response as necessary.

What You Bring

You should have extensive experience in security research, ML for audio/video analysis, and familiarity with Python and ML frameworks. A strong academic background coupled with hands-on experience in production systems is essential.

Preferred Qualifications

  • Publications, patents, or presentations in relevant fields.
  • Experience with big data platforms and synthetic media detection.
  • Expertise in adversarial ML and real time performance constraints.

Microsoft Culture & Values

At Microsoft, a growth mindset, collaboration, and accountability drive everyday innovation and inclusion, ensuring every team member can thrive.

Key skills/competency

  • Deepfake Detection
  • ML Systems
  • Audio/Video Analysis
  • Security Research
  • Data Science
  • Prototype Development
  • Incident Response
  • Benchmarking
  • Python
  • Big Data
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How to Get Hired at Microsoft

🎯 Tips for Getting Hired

  • Customize your resume: Tailor your skills to security research.
  • Highlight ML expertise: Emphasize Python and ML framework experience.
  • Showcase project impact: Detail production system contributions.
  • Research Microsoft: Understand culture, innovations, and security projects.

📝 Interview Preparation Advice

Technical Preparation

Study advanced ML algorithms.
Practice Python coding challenges.
Review deepfake detection literature.
Experiment with ML model prototypes.

Behavioral Questions

Explain a challenging collaboration experience.
Describe handling tight deadlines under pressure.
Discuss conflict resolution in teams.
Share an example of innovative problem solving.

Frequently Asked Questions