Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build and optimise cutting-edge recommendation systems for a dynamic retail platform.
- Company: Join a fast-growing Series A Scale-Up in the exciting retail sector.
- Benefits: Competitive salary up to £150k, equity options, and hybrid working in Central London.
- Other info: Exciting opportunity for career growth in a collaborative team.
- Why this job: Perfect for ML enthusiasts eager to make an impact in a rapidly scaling environment.
- Qualifications: Strong ML background and experience with recommendation systems required.
The predicted salary is between 90000 - 150000 £ per year.
OB have partnered with a Series A Scale-Up in the Retail space, who are looking to expand their ML function as they continue to scale their platform. You will take a high degree of ownership over the ML function, building solutions for personalisation features on the platform. This is a perfect role for a true ML enthusiast, where you'll have the opportunity to build Recommendation and Ranking systems in production environments, where you will use your foundation of Data Science and ML to work closely with the wider team.
Key skills and experience:
- Strong background in Machine Learning
- Experience building or working on Recommendation/Ranking systems
- Ideally experience in scaling organisations
- Strong academic background in STEM, from a Top ranked University
Salary - Base salary of £90k-£150k + equity (depending on skills and experience)
Hybrid working in Central London
To be considered, you must be UK based and Visa sponsorship is unavailable.
ML Engineer - Recommender Systems - Up to £150k in City of London employer: Oliver Bernard
Contact Detail:
Oliver Bernard Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer - Recommender Systems - Up to £150k in City of London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working in ML or at companies you're interested in. A friendly chat can lead to opportunities that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially any work related to recommendation and ranking systems. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common ML interview questions and be ready to discuss your past experiences in detail. Confidence is key!
✨Tip Number 4
Don't forget to apply through our website! We have loads of exciting opportunities, and applying directly can sometimes give you an edge. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace ML Engineer - Recommender Systems - Up to £150k in City of London
Some tips for your application 🫡
Show Your Passion for ML: Let us see your enthusiasm for machine learning! In your application, share specific projects or experiences that highlight your love for building recommendation and ranking systems. We want to know what drives you in this field!
Tailor Your CV: Make sure your CV is tailored to the role. Highlight relevant experience in ML and any work you've done with recommendation systems. We appreciate when candidates take the time to align their skills with what we're looking for.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're the perfect fit for our team. Share your vision for how you can contribute to our ML function and make an impact on personalisation features.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen to join our team!
How to prepare for a job interview at Oliver Bernard
✨Know Your ML Stuff
Make sure you brush up on your machine learning fundamentals, especially around recommendation and ranking systems. Be ready to discuss your past projects and how you've applied ML techniques in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare to tackle some technical questions or case studies during the interview. Think about how you would approach building a recommendation system from scratch and be ready to explain your thought process clearly.
✨Understand the Company’s Product
Do your homework on the company’s platform and its personalisation features. Being able to discuss how you can contribute to their specific needs will show that you're genuinely interested and invested in the role.
✨Ask Insightful Questions
Prepare a few thoughtful questions about the team dynamics, the challenges they face in scaling their ML function, and how they measure success. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.