Machine Learning Integration Engineer (Cybersecurity)

TL;DR

Machine Learning Integration Engineer (Cybersecurity): Deploying and optimizing innovative machine learning models to enhance cybersecurity services with an accent on runtime performance and scalability. Focus on collaborating with cross-functional teams to prototype new ideas and advance methodologies for defending against unknown cyber-attacks.

Location: Hybrid position, must be able to attend the Cambridge office at least 2 days a week.

Company

hirify.global is a global leader in AI for cybersecurity, protecting nearly 10,000 organizations from unknown threats using its proprietary Active AI Security Platform.

What you will do

• Deploy and optimize new machine learning models to improve service offerings.
• Collaborate with engineers, ML specialists, and security researchers to create cutting-edge solutions.
• Prototype new ideas and optimize runtime and memory usage of existing models.
• Advance unique methodologies for defending against unknown cyber-attacks.
• Develop core competencies across various technology stacks.

Requirements

• Must be able to work from the Cambridge office at least 2 days a week.
• Proficiency in writing production-quality Python code.
• Experience with machine learning and model acceleration frameworks such as PyTorch, ONNX, and ONNX Runtime.
• Strong experience with Python data and matrix manipulation libraries like numpy and pandas.
• Ability to work autonomously and collaborate effectively within a cross-functional team.
• Interest in cybersecurity and willingness to learn.

Nice to have

• Knowledge of Python memory management and GPU optimization.
• Experience with Rust, specifically the ort crate.

Culture & Benefits

• 23 days of holiday plus public holidays, increasing to 25 days after 2 years.
• Private medical insurance for you and your family.
• Life insurance at 4x base salary.
• Salary sacrifice pension scheme and enhanced family leave.
• Cycle to work scheme and confidential Employee Assistance Program.