Senior Machine Learning Researcher

Overview

In this role you will drive research and prototype development in AI-driven cybersecurity, collaborating with software and security teams to translate research into deployable solutions. You’ll explore ML techniques, including large language models, and implement models in the broader software stack with edge deployment optimization. The position blends independent research with cross-functional teamwork in a hybrid Cambridge-based setup. You will help shape Darktrace’s distinctive cyber defence approach and deliver latency- and memory-efficient AI systems.

Pay / Benefits

• 23 days’ holiday
• Birthday day off
• Private medical insurance
• Life insurance 4x base salary
• Salary sacrifice pension scheme
• Enhanced family leave

Responsibilities

• Explore and solve problems using ML techniques across domains (LLMs, statistical methods, classical ML)
• Conduct independent research and collaborative work with cross-functional teams
• Implement ML models within the wider software stack and ensure deployment readiness
• Develop optimised solutions for edge devices focusing on latency and memory
• Collaborate with software engineers and security analysis teams to test and implement research outcomes

Key requirements

• PhD or Master’s in Machine Learning or related discipline (or equivalent experience)
• Experience with Python ML libraries (PyTorch, TensorFlow, scikit-learn)
• Strong understanding of large language models and applications (transfer learning, embeddings, generative usage, agentic functionality)
• Ability to work autonomously while being a team player
• Familiarity with Linux and Git (desirable for workflow)
• Basic understanding of cybersecurity concepts and AI-specific threats (desirable)

• 团队协作能力
• 自主决策能力
• 良好沟通研究成果
• PyTorch
• TensorFlow
• scikit-learn

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