About the Role

Lead end-to-end AI model development for security scenarios, including privacy-aware data curation, continual pretraining, fine-tuning, and reinforcement learning. Drive training efficiency on distributed GPU systems, embed responsible AI, and translate innovations into shipped experiences. Mentor scientists and engineers to scale results across globally distributed teams.

Key Responsibilities

• Execute full modeling lifecycle for security scenarios from data ingestion to deployment and monitoring
• Design and operate privacy-preserving data workflows including anonymization and synthetic augmentation
• Develop fine-tuning and adaptation recipes for transformer models including reinforcement learning
• Contribute to objective benchmarks and automated gates for accuracy, robustness, safety, and performance
• Collaborate with engineering and product teams to productionize models and meet service-level objectives

Required Skills & Qualifications

Must Have:

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience OR equivalent
• 5+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers)
• Proficiency in Python and PyTorch with hands-on experience building and debugging large-scale training jobs
• Ability to pass Microsoft Cloud Background Check upon hire and every two years thereafter

Nice to Have:

• Security domain experience in areas like security operations, threat intelligence, malware analysis, or cloud identity
• Experience with distributed training and scaling techniques like DeepSpeed, FSDP, ZeRO, and model parallelism
• Experience with privacy preserving ML including differential privacy concepts and privacy risk assessment

Benefits & Perks

• Industry leading healthcare