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. To learn more, visit http://www.darktrace.com.  

Job Description:

As a Specialist Machine Learning Researcher, you will play a pivotal role in driving innovation across diverse projects, ranging from rapid prototyping of new ideas to large-scale research initiatives. Working closely with software engineers, you will test and implement research outcomes, contributing to our unique cyber defence methodology. While this position emphasizes deep expertise in machine learning, it also involves extensive collaboration with software development and security analysis teams.

Please note: This is a hybrid role, requiring compulsory attendance of 2 days per week at our Cambridge office.

What will I be doing?

You will be responsible for designing and implementing cutting-edge solutions to complex problems across multiple domains. This includes leveraging advanced techniques such as large language models (LLMs), statistical methods, and classical machine learning where appropriate. You will work both independently as a researcher and collaboratively within cross-functional teams. Additionally, you will integrate your machine learning models into the broader software stack, ensuring seamless deployment.

As our models are deployed in varied environments—including edge devices—you will be expected to deliver optimized solutions that balance latency, memory efficiency, and performance.

Other responsibilities include (but are not limited to):

• Designing robust evaluation frameworks to measure model performance and reliability across diverse use cases,
• Staying up to date with emerging trends in AI/ML and proactively recommending improvements to existing systems,
• Collaborating with engineering teams to ensure scalability, security, and maintainability of deployed solutions.

What experience do I need?

Candidates should ideally hold a PhD or Master’s degree in machine learning or a related discipline, or possess equivalent practical experience. You must demonstrate strong proficiency with Python machine learning libraries such as PyTorch, TensorFlow, and scikit-learn, along with a deep understanding of large language models and their applications—including transfer learning, embeddings, generative usage, and agentic functionality. The ideal candidate will be a collaborative team player while also capable of working autonomously and making independent decisions.

Additional desirable experience includes:

• Familiarity with agentic system tooling (e.g., LangGraph, LangChain, smolagents) and supporting infrastructure (MCP servers, vector databases, memory, ontologies)
• Experience with cloud AI services (AWS Bedrock, Azure AI Foundry, Vertex AI, Copilot Studio) and diverse ML techniques,
• Working knowledge of Linux, Git, and basic cybersecurity concepts, including AI-specific 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.