Take responsibility for the planning and delivery of long and short-term research projects, including:
Improving assistant behavior through privacy-preserving feedback
Automatic gathering of threat and process intelligence
Methods for ranking diverse work items to maximize security
Novel LLM-based detection frameworks
Provide technical Leadership and Guidance: establishing research and coding standards, system design principles, and best practices; guiding your teams in overcoming technical challenges while ensuring that our research base remains efficient and maintainable
Drive Solution Architecture and Design: designing research programs and systems that meet the requirements of a diverse stakeholder group
Lead Collaboration and communication: collaborating closely with other group members and stakeholders including project managers, product owners, and other engineering teams; ensuring that technical options and decisions, and project timelines, are clearly communicated to all stakeholders
Model Continuous Learning and Skill Development: helping the group and the broader team to stay up-to-date with the latest tools and techniques in both the machine learning and security fields; fostering a culture of continuous learning and skill development; mentoring more junior colleagues
Requirements & Skills:
Master’s or Doctoral Degree in a quantitative science or engineering field.
10+ years of experience solving complex problems using modern AI/ML techniques; at least five of them managing teams.
Experience with the full system development lifecycle, from requirement gathering, research, design, implementation, and testing, through deployment/launch and operation
Comfort working cross-functionally with Product and other Engineering teams.
Complete mastery of a subset of the languages, frameworks, and tools currently used in the development of data-intensive, machine learning systems, e.g. Spark, Airflow, Python, TensorFlow/PyTorch.
Ability to communicate project needs, status, outcomes, and implications to technical and non-technical audiences, inside and outside the company.
First-author publications at peer-reviewed AI conferences
Expertise in natural language processing, especially practical experience developing or tuning modern, transformer-based language or multi-modal models
