Senior Machine Learning Researcher

Description

Darktrace is a global leader in AI-driven cybersecurity, helping organizations stay ahead of evolving threats every day.

Darktrace was built on a genuinely differentiated idea: that Adaptive AI could detect and respond to novel, real-time cyber threats. That approach matters more than ever in the era of AI. Today, our customers depend on us to stay ahead.

At Darktrace, we are energized by that responsibility. We work across teams and rally around a shared goal. We own outcomes end to end - step in, step up and see things through without waiting to be asked. We make decisions with urgency, say the hard thing, and hold each other to high standards with care and directness. We move first and learn fast anticipating where our customers are going next, continuously challenging ourselves.

We invest in the skills, learning and opportunities that help people deliver at the level their roles demand, and reward the aptitude and curiosity to grow beyond them.

Our Values: Own It | Win as One | Raise Our Bar | Move First. Learn Fast

Job D escription :

As a Senior 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.

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. 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?

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)

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:

Familiarity with standard tooling for agentic systems.and associated infrastructure (e.g. MCP servers, vector databases, memory, ontologies)

Experience with low-code and high-code cloud AI services (e.g. AWS Bedrock, Azure AI Foundry, Vertex AI, Copilot Studio)

Experience with a variety of machine learning techniques

Familiarity with Linux and Git

Basic understanding of cybersecurity concepts and common threats, including those specific to AI systems

Conditions

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.

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,