Specialist Machine Learning Researcher

Darktrace Specialist Machine Learning Researcher

Darktrace is a global leader in AI for cybersecurity that keeps organizations ahead of the changing threat landscape every day. Founded in 2013, Darktrace provides the essential cybersecurity platform protecting nearly 10,000 organizations 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.

As a Specialist Machine Learning Researcher, you'll play a key role in diverse projects, from prototyping new ideas to extensive research initiatives. 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.

Please note this is a hybrid role, with a compulsory attendance of 2 days a week in the Cambridge office.

What will I be doing:

You will be responsible for exploring solutions to interesting problems in a variety of domains, using techniques including large language models, statistical methods, and classical machine learning where appropriate. You will work both as an independent researcher and in team collaborations. Other responsibilities will include but not limited to:

• Integrating your machine learning models into the broader software stack,
• Optimising solution, since our models are deployed across a variety of environments, including edge devices,
• Optimising for both low latency and minimal memory usage.

What experience do I need:

• 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)
• A deep understanding of large language models and their applications (e.g. transfer learning, embeddings, generative usage, agentic functionality)
• Be a team player but with the ability to operate autonomously and take independent decisions.

Desirable experience includes familiarity with standard tooling for agentic systems—such as LangGraph, LangChain, and smolagents, as well as the supporting infrastructure including MCP servers, vector databases, memory components, and ontologies. It is also beneficial to have experience working with both low‑code and high‑code cloud AI services like AWS Bedrock, Azure AI Foundry, Vertex AI, and Copilot Studio. A solid grounding in a variety of machine learning techniques is valuable, along with being comfortable using Linux and Git. Additionally, a basic understanding of cybersecurity concepts and common threats, particularly those relevant to AI systems, would be highly advantageous.

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.