At a Glance
- Tasks: Explore innovative machine learning solutions to tackle real-world cybersecurity challenges.
- Company: Join Darktrace, a global leader in AI-driven cybersecurity.
- Benefits: Enjoy 23 days holiday, private medical insurance, and a birthday day off.
- Other info: Hybrid role with opportunities for professional growth and collaboration.
- Why this job: Make a real impact in cybersecurity while working with cutting-edge AI technology.
- Qualifications: PhD or master's in machine learning, plus experience with Python libraries.
The predicted salary is between 63000 - 77000 £ per year.
Darktrace is a global leader in AI-driven cybersecurity, helping organisations 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. Today, our customers depend on us to stay ahead. At Darktrace, we are energised 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
As a Machine Learning Researcher, you'll play a key role in diverse projects, from prototyping new ideas to improving existing projects. 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 language models, neural networks, 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?
We are looking for a curious and motivated machine learning professional with a strong academic or industry background in AI, machine learning, or a related field. You will be comfortable applying machine learning techniques to solve complex real-world problems, working collaboratively within a multidisciplinary team, and communicating technical concepts to a range of stakeholders. A proactive approach to learning, problem-solving, and innovation will be key to success in this role.
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).
- Experience with a variety of machine learning techniques.
- Be a team player but with the ability to operate autonomously and take independent decisions.
Desirable:
- Familiarity with Linux and Git.
- Basic understanding of cybersecurity concepts and common 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.
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, colour, 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.
Machine Learning Researcher employer: Darktrace
Darktrace is an exceptional employer, offering a dynamic work environment where innovation thrives and employees are empowered to contribute to cutting-edge AI cybersecurity solutions. With a strong focus on employee well-being, the company provides generous benefits including private medical insurance, enhanced family leave, and a supportive culture that encourages professional growth and collaboration. Located in vibrant London or Cambridge, employees enjoy a hybrid work model that fosters flexibility while being part of a global team dedicated to staying ahead of the evolving threat landscape.
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We think this is how you could land Machine Learning Researcher
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We think you need these skills to ace Machine Learning Researcher
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Darktrace. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
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✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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✨Get Comfortable with Python and R
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
