At a Glance
- Tasks: Design and build recommendation systems that shape user experiences.
- Company: Join a dynamic startup with a focus on innovation and growth.
- Benefits: Competitive salary, career support, and opportunities in high-growth tech.
- Other info: Work in a small team with high autonomy and rapid deployment.
- Why this job: Make a real impact by personalising user experiences with cutting-edge AI.
- Qualifications: Experience in building recommendation systems and a strong ML foundation.
The predicted salary is between 59400 - 72600 £ per year.
You'll own the algorithms that decide what every user sees. That means designing, building and shipping recommendation and personalisation systems end-to-end — from problem framing and feature design through to production deployment, monitoring and iteration. You'll work alongside a dedicated Data Engineer who builds the pipelines and architecture underneath you, and you'll report into a small, senior team where your work goes live quickly.
What you'll do:
- Design and productionise recommendation engines and personalisation algorithms for a consumer-facing platform.
- Take models from experiment to production, and own their performance once they're there.
- Decide what signals matter, and work with the Data Engineer to get them modelled and available.
- Run experiments and measure real impact on user behaviour, not just offline metrics.
- Apply modern agentic and LLM-based approaches where they genuinely improve outcomes.
What we're looking for:
- Demonstrable experience building and productionising recommendation systems or personalisation algorithms for apps or websites — shipped, live, used by real users.
- A genuine Machine Learning and Data Science foundation — you were solving these problems before the ChatGPT era, not just calling APIs.
- Background from a consumer platform where behavioural data is the core asset — social platforms, marketplaces, travel, large-scale consumer tech.
- Comfortable operating as an IC in a small team with high autonomy.
- AI-native in practice: fluent with agentic tooling and able to use it to move faster.
Nice to have:
- Experience applying agent-based approaches to recommendations or personalisation.
- Experience at a company that scaled from Series B through C/D/E.
Why work with Calyptus?
- Access opportunities with ambitious startups and high-growth technology companies.
- Direct support from experienced specialist recruiters.
- Honest feedback and clear communication throughout the hiring process.
- Long-term career support, not just a single job application.
AI Engineer, Personalisation & Recommendations employer: Calyptus
Calyptus is an exceptional employer for Senior Backend Engineers, offering a dynamic work environment where innovation thrives. With a focus on ambitious startups and high-growth technology companies, employees benefit from direct support from experienced recruiters, fostering both personal and professional growth. The collaborative culture encourages mentorship and the opportunity to shape cutting-edge AI-powered investment tools, making it a rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer, Personalisation & Recommendations
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Calyptus or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Calyptus.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Calyptus.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Calyptus that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace AI Engineer, Personalisation & Recommendations
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Calyptus.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Calyptus and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Calyptus
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Calyptus uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
