Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

AI Engineer II - Model R&D

Rapid7
Belfast
1 year ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer II, Marketing Testing

Machine Learning Engineer III

Machine Learning Engineer III

Machine Learning Engineer III

Senior Machine Learning Engineer, AI Infrastructure, Autonomy

Machine Learning Researcher

The global order relies on a free and open internet, and cybercriminals have turned it into their playground. As they chase AI to increase the speed and scale of their attacks, Rapid7 has been leveraging it to supercharge our cybersecurity detections and triage alerts quickly. For decades, we’ve been using AI technology to power risk and threat analysis to detect attacks earlier and reduce response time.

Rapid7 is making significant investments in our Belfast office with the formation of our new AI Centre of Excellence, encompassing the full range of AI, ML and data science.

As a leader in cybersecurity, we’re on a new mission to use AI to accelerate threat investigation, detection and response (D&R) capabilities of our Security Operations Centre (SOC). The AI race to stay ahead of attackers is on and needs more than speed. Attack surfaces are getting broader every day and it’s important to optimise D&R with AI that can identify signals in a sea of noise. Further, we’re embracing generative AI and researching novel ways LLMs can add value for our customers in D&R.

We’re seeking the best AI, ML and data science talent to build systems for detecting patterns and anomalies humans can't, and which rule-based detections miss. As an AI Engineer II, you will work on solutions that address important challenges, working closely with development teams, data engineering, product managers and UI/UX teams along the way. There’s a ton of work to do and we would love you to join us!

Rapid7’s AI Centre of Excellence

The AI CoE partners with our D&R teams in enabling customers to assess risk, detect threats and automate their security programs. Rapid7 also have a best-of-breed managed SOC offering, known as MDR, where teams of analysts are retained to carry out crucial D&R work on behalf of our customers. The positive impact of AI in D&R will be felt right across our customer base. The AI CoE’s goals are ambitious and we need dynamic people with a desire to be part of something big. You have a chance to join a company that’s pushing the boundaries of AI for cybersecurity - if you want a career move where you can grow and make an impact with AI, this is it.

We ensure AI, ML and data science are applied in a meaningful way to add customer value, best achieve business objectives and deliver ROI. Unnecessary complexity is avoided and we adopt a creative, fast-fail, highly iterative approach to accelerate ideas from proof-of-concept to go or no-go. Our current capabilities are built on 20+ years of threat analysis and open-source communities with, 40 AI patents granted and 20+ pending. However, we’re just getting started!

The make-up of the group is such that our technical skills complement one another. No one can be an expert in everything - we share our AI, ML and data science knowledge between ourselves plus are creating an in-house AI Learning & Development plan. The AI CoE also contributes on occasion to new external AI policy initiatives with recognised bodies like NIST. In fact, we’d be delighted if you’re open to publishing and presenting your best work with Rapid7 at top conferences around the world and in journals. Our current AI team have a track record of publishing award-winning research at the likes of AISec at ACM CCS and with IEEE; we realise the benefits publishing can bring to an AI career and the confidence it inspires in our customers.

About the Role

An AI Engineer II in Model R&D designs and implements AI models that are appropriate for the task at hand, using conventional machine learning, deep learning neural networks and other data science techniques, depending on where their skills lie. 

This is greenfield work and speed to market is key - you’ll work fast and smart, supported by more senior members of the team, getting results that let us make decisions about what to start, what to stop, and what to look into more closely. You will have the freedom to take risks and be wrong; even if experiments don’t work out, we iterate and try again. Model R&D happens both locally and in the cloud using IDEs and Jupyter, GPU compute as needed, and deployment to production using cloud services like AWS.

You will:

Research and develop AI/ML/data science models with a focus on delivering customer value.

With guidance and direction, you are able to explore, research and tackle problems while building up your knowledge.

Take responsibility for the quality of your own work and help impact the work of others too.

Be a first-class stakeholder in all parts of the AI R&D process.

Create productive cross-functional relations with teams like engineering, UX, customer research and product management.

Provide informal guidance to new team members.

What we’re looking for technically:

Good conceptual knowledge of a particular field of AI/ML/data science with applied experience. It’s a broad area; we do not expect you to be across it all.

More specifically, building models using Python and any libraries like:

scikit-learn/sklearn; for more conventional ML and data science.

PyTorch/Tensorflow/Keras; if your background is deep learning and neural networks.

Huggingface/Transformers/LangChain; we use these for LLMs.

Pandas/NumPy; for pre-processing and massaging data.

As a bonus, a PhD or MSc using AI/ML/data science. We’re completely open-minded if you’ve got a Software Engineering or related degree and changed lanes into AI.

Any cybersecurity expertise is also a bonus - or maybe your experience comes from capital markets, online marketplaces, healthcare, social media, insurance, or somewhere else.

And you as a person:

Bring a positive, can-do, solution-oriented mindset, welcoming the challenge of tackling new problems.

Are persistent and consistent.

Enjoy working in a fast-paced environment.

Understand the highly iterative nature of AI development and the need for rigour.

Appreciate the importance of thorough testing and evaluation to avoid silent failures in model development.

Are a great teammate to help peers become stronger problem solvers, communicators, and collaborators.

Have a curiosity and passion for continuous learning and self-development.

Stay open-minded, listening to new ideas and suggestions from colleagues, carefully considering and sometimes adopting them.

Realise the importance of wider ethical and risk considerations with AI.

Possess good interpersonal and communication abilities, explaining hard-to-understand topics to different audiences and writing up work clearly.

Exhibit a bias for action, without being careless.

We know that the best ideas and solutions come from multi-dimensional teams. That’s because these teams reflect a variety of backgrounds and professional experiences. If you are excited about this role and feel your experience can make an impact on our AI mission, please don’t be shy - apply today.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.

AI Team Structures Explained: Who Does What in a Modern AI Department

Artificial Intelligence (AI) and Machine Learning (ML) are no longer confined to research labs and tech giants. In the UK, organisations from healthcare and finance to retail and logistics are adopting AI to solve problems, automate processes, and create new products. With this growth comes the need for well-structured teams. But what does an AI department actually look like? Who does what? And how do all the moving parts come together to deliver business value? In this guide, we’ll explain modern AI team structures, break down the responsibilities of each role, explore how teams differ in startups versus enterprises, and highlight what UK employers are looking for. Whether you’re an applicant or an employer, this article will help you understand the anatomy of a successful AI department.

Why the UK Could Be the World’s Next AI Jobs Hub

Artificial Intelligence (AI) has rapidly moved from research labs into boardrooms, classrooms, hospitals, and homes. It is already reshaping economies and transforming industries at a scale comparable to the industrial revolution or the rise of the internet. Around the world, countries are competing fiercely to lead in AI innovation and reap its economic, social, and strategic benefits. The United Kingdom is uniquely positioned in this race. With a rich heritage in computing, world-class universities, forward-thinking government policy, and a growing ecosystem of startups and enterprises, the UK has many of the elements needed to become the world’s next AI hub. Yet competition is intense, particularly from the United States and China. Success will depend on how effectively the UK can scale its strengths, close its gaps, and seize opportunities in the years ahead. This article explores why the UK could be the world’s next global hub for artificial intelligence, what challenges it must overcome, and what this means for businesses, researchers, and job seekers.