Machine Learning Researcher (Cybersecurity)

TL;DR

Machine Learning Researcher (Cybersecurity): Developing and prototyping novel AI solutions for real-time cyber threat detection and response with an accent on neural networks, language models, and statistical methods. Focus on implementing optimized ML models for the wider software stack and edge devices, balancing latency and memory constraints.

Location: Cambridge, UK (Hybrid: compulsory attendance of 2 days a week in the Cambridge office)

Company

A global leader in AI-driven cybersecurity providing an Adaptive AI platform to protect organizations from unknown threats.

What you will do

• Explore and prototype solutions for complex problems using LMs, neural networks, and classical ML.
• Implement research outcomes into the wider software stack in collaboration with software engineers.
• Optimize ML models for latency and memory, especially for deployment on edge devices.
• Conduct independent research while collaborating within multidisciplinary teams.
• Contribute to the development of a distinctive cyber defense methodology.

Requirements

• PhD or Master's degree in Machine Learning or a related discipline (or equivalent experience).
• Proficiency with Python ML libraries such as PyTorch, TensorFlow, and scikit-learn.
• Proven experience applying various machine learning techniques to real-world problems.
• Ability to operate autonomously and make independent technical decisions.
• Strong communication skills to convey technical concepts to various stakeholders.

Nice to have

• Familiarity with Linux and Git.
• Basic understanding of cybersecurity concepts and common threats.

Culture & Benefits

• Vacation: 23 days’ holiday (rising to 25 after 2 years) plus all public holidays and a day off for your birthday.
• Health: Private medical insurance covering the employee, cohabiting partner, and children.
• Financial: Life insurance (4x base salary) and a salary sacrifice pension scheme.
• Well-being: Confidential Employee Assistance Program and Cycle to work scheme.
• Family: Enhanced family leave policies.