Ph.D. degree AND 3+ year's experience (or Master's AND 6+ years' experience, or Bachelor's AND 8+ years' experience, or 10+ years of equivalent experience) in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field with specialization in natural language processing/computer vision/multimodal analysis/deep learning/machine learning
Strong algorithmic problem solving and software development skills (Python/Java/C++). Proficiency with open-source tools such as PyTorch Experience with statistical analysis and data visualization tools
Excellent verbal and written communication skills
Preferred/Additional Qualifications:
Publication(s) in top-tier conferences or journals in related fields (e.g., ACL, EMNLP, CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, AAAI, etc.).
Industry experience with large-scale data processing, distributed computing, or cloud platforms
Experience with OpenAI GPT(Generative Pre-trained Transformer models), Azure AI Services
Strong people leadership skills to influence others, with the ability to understand team dynamics, retain, attract, and develop team members.
Strong experience in leading applied science or research teams, preferably in the field of responsible AI
Responsibilities
Drive the development and execution of the team's research agenda, prioritizing projects that address responsible AI challenges
Lead and contribute to research projects focused on developing innovative techniques and methodologies for both the measurement and mitigation of AI risks
Stay up-to-date with the latest advancements in responsible AI research and industry best practices
Collaborate with internal and external stakeholders to ensure responsible AI practices are integrated into the development and deployment of AI solutions
Support hiring, coaching, mentoring and career development of Applied Scientists and Software Engineers to build inclusive and ambitious applied science focused teams
Provide technical guidance and mentorship to the team, fostering a culture of innovation, collaboration, and continuous learning
Internalize and champion Microsoft's culture and values