Senior / Principle Security Research - Agent ML Team (Cortex)

Are you passionate about using cutting-edge technology to help protect the world against cyber threats? Do you live and breathe the cyber security world? Do you want to take part in an innovative and disruptive AI security group that has an impact on many customers?
You will be part of a strong security research and data science team who solve highly complex security challenges using disruptive technologies, AI & ML algorithms and a lot of data.
As part of that, you will take part in the design and development of new groundbreaking AI security solutions which make a direct impact on many customers.
At Palo Alto Networks we value diverse viewpoints and experiences, as we are solving complex cyber security challenges. We are committed to a safe and inclusive workspace.
Key Responsibilities
Be at the forefront of security innovation, building next-gen detection capabilities powered by AI, deep-learning, machine learning, big data, and deep threat intelligence.
Dive deep into low-level s

דרישות:

Required Qualifications
At least 5 years of experience in cyber security research space
At least 3 years of experience with endpoint security research or offensive \ defensive low-level, file related realms
Proven experience in the low level world, including OS internals, dynamic and static analysis of malware and software and reverse engineering
Proven experience in running end-to-end research POCs from ideas to customer impact solutions including the design, execution, analysis and conclusions of your research, methodologies and outcomes
Investigation skills and critical thinking using analytics, data mining, and data interpretation
Familiarity with analysis of various file types
Proficient hands-on coding skills in Python
Experience with SQL or related query languages
Excellent communication skills - ability to present research results in a clear and meaningful manner
Preferred Qualifications
Proficiency in C \ CPP
Experience with data-driven or ML models
Experience with big data p