Darktrace

Machine Learning Researcher

In short

Machine Learning Researcher role at Darktrace, an AI-driven cybersecurity company, based in their Cambridge office with a hybrid schedule requiring 2 days a week on-site. The role involves researching and prototyping ML solutions using language models, neural networks, statistical methods and classical ML, then implementing them into the software stack, including optimised deployments on edge devices. Requires a PhD or master's degree in machine learning or related field (or equivalent experience) and hands-on experience with Python ML libraries like PyTorch, TensorFlow or scikit-learn.

About Darktrace
Darktrace is a global leader in AI for cybersecurity that keeps organisations ahead of the changing threat landscape every day. Founded in 2013, Darktrace provides the essential cybersecurity platform protecting nearly 10,000 organisations from unknown threats using its proprietary AI.
The Darktrace Active AI Security Platform™ delivers a proactive approach to cyber resilience to secure the business across the entire digital estate – from network to cloud to email. Breakthrough innovations from our R&D teams have resulted in over 200 patent applications filed. Darktrace's platform and services are supported by over 2,400 employees around the world.
Role
As a Machine Learning Researcher, you'll play a key role in diverse projects, from prototyping new ideas to improving existing projects. Collaborating with software engineers, you'll test and implement research outcomes, contributing to our distinctive cyber defence methodology. This position emphasises expertise in machine learning, though will also involve extensive collaboration with software development and security analysis teams.
What will I be doing?
You will be responsible for exploring solutions to interesting problems in a variety of domains, using techniques including language models, neural networks, statistical methods, and classical machine learning where appropriate. You will work both as an independent researcher and in team collaborations. You will also be responsible for implementing your machine learning models in the wider software stack. As we deploy our machine learning models in a variety of settings, including on edge devices, you will be expected to produce optimised solutions for both latency and memory.
Please note this is a hybrid role, with a compulsory attendance of 2 days a week in the Cambridge office.
What experience do I need?
We are looking for a curious and motivated machine learning professional with a strong academic or industry background in AI, machine learning, or a related field. You will be comfortable applying machine learning techniques to solve complex real-world problems, working collaboratively within a multidisciplinary team, and communicating technical concepts to a range of stakeholders. A proactive approach to learning, problem-solving, and innovation will be key to success in this role.
Essential:
•Candidates must have a PhD or master's degree in machine learning or a related discipline or equivalent experience.
•Experience with Python machine learning libraries (e.g. PyTorch, TensorFlow, scikit-learn)
•Experience with a variety of machine learning techniques.
•Be a team player but with the ability to operate autonomously and take independent decisions.
Desirable:
•Familiarity with Linux and Git
•Basic understanding of cybersecurity concepts and common threats
Benefits
•23 days' holiday + all public holidays, rising to 25 days after 2 years of service
•Additional day off for your birthday
•Private medical insurance which covers you, your cohabiting partner and children
•Life insurance of 4 times your base salary
•Salary sacrifice pension scheme
•Enhanced family leave
•Confidential Employee Assistance Program
•Cycle to work scheme
As a growing business strengthening its governance and controls, this role plays a part in supporting high standards of integrity and accountability.

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