Job Description

THE ROLE:

The FireEye Data Science Intern will lead research and development into methods for hardening next-gen AV systems against adversarial evasion attacks. Specifically, the intern will combine state-of-the-art methods from transfer learning, adversarial example generation, and data poisoning attacks to develop a new method to collaboratively 'immunize' next-gen AV systems against adversarial attacks. As part of this role, the intern will be expected to read, understand, and apply techniques from recent research papers and develop a system for training malware classifier against adversarial attacks.

RESPONSIBILITIES:

The intern will be expected to:

• Interact with senior members of the Data Science team to identify potential avenues of research inquiry
• Implement new research ideas as prototype code to demonstrate efficacy of approach
• Present research results to the project team and larger data science team for peer review
• Write a white paper describing the novel methods developed during the internship and present the results as a poster at the conclusion of the internship
• Participate in weekly team meetings and journal clubs, providing feedback on FireEye Data Science projects

Qualifications

REQUIREMENTS:

• Experience in applying machine learning techniques to security problems, particularly malware detection
• Understanding of attacks on machine learning models, including data poisoning and adversarial example generation
• Strong Python development skills using standard machine learning packages
• Experience with Linux and Jupyter notebooks
• Strong written and verbal communication skills
• Ability to document and explain technical concepts clearly and concisely
• Ability to work as part of a remote team
• Must be a continuing college or university student in good standing at an accredited institution pursuing a Master's or PhD degree

Additional Information

All your information will be kept confidential according to EEO guidelines.