Senior Machine Learning Researcher Software

Frontdoor Defense; Cambridge; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

23 days holiday

Private medical insurance

Life insurance

Salary sacrifice pension

Cycle to work

Job summary

Darktrace is seeking a Senior Machine Learning Researcher in Cambridge. You will lead development of ML models from research to deployment within our software stack, collaborating with software and security teams to implement outcomes and optimize performance for latency and memory, including edge deployments.

This hybrid role requires 2 days per week in the Cambridge office. A PhD or Master’s in ML or related field, and strong Python ML library experience are essential.

Qualifications

• PhD or master's degree in machine learning or a related discipline (or equivalent experience).
• Strong experience with Python ML libraries (PyTorch, TensorFlow, scikit-learn).
• Deep understanding of large language models and their applications.
• Ability to work autonomously and as part of a team.

Responsibilities

• Lead development of ML models from research to deployment within the software stack.
• Test and implement research outcomes within the software stack.
• Collaborate with software engineers and security analysis teams.
• Develop optimized ML solutions for latency and memory, including edge deployments.

Skills

Python ML libraries

Large language models

Autonomous work

Team collaboration

Education

PhD or Master’s in ML or related

Job description

Senior Machine Learning Researcher

Lead development of ML models from research to deployment within Darktrace's software stack

Location: Cambridge, England

About The Role

Senior Machine Learning Researcher

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 Description:

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

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.

Darktrace is an Equal Opportunity Employer. We consider all qualified applicants for employment without regard to race, color, religion, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, veteran or military status, or any other characteristic protected by applicable federal, state, or local law.

Darktrace is committed to providing reasonable accommodations to qualified individuals with disabilities in accordance with applicable laws. If you require a reasonable accommodation to participate in the application or interview process, please contact your Talent Partner.