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- Tasks: Build and optimise ML solutions for personalisation features in a dynamic retail platform.
- Company: Exciting Series A Scale-Up in the Retail sector, focused on innovation.
- Benefits: Competitive salary, equity options, and hybrid working in Central London.
- Other info: Perfect for ML enthusiasts looking for growth in a scaling organisation.
- Why this job: Join a passionate team and make a real impact with cutting-edge ML technologies.
- Qualifications: Strong background in Machine Learning and experience with Recommendation/Ranking systems.
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 employer: Oliver Bernard
Contact Detail:
Oliver Bernard Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer - Recommender Systems
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with ML enthusiasts on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those 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 technical interviews by brushing up on your ML concepts and coding skills. Practice common interview questions and work on real-world problems to demonstrate your expertise during the interview process.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications!
We think you need these skills to ace ML Engineer - Recommender Systems
Some tips for your application 🫡
Show Your Passion for ML: Let your enthusiasm for machine learning shine through in your application. We want to see how excited you are about building recommendation and ranking systems, so share any personal projects or experiences that highlight your passion!
Tailor Your CV: Make sure your CV is tailored to the role. Highlight your experience with ML and any relevant projects you've worked on, especially those related to recommendation systems. We love seeing how your background aligns with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you're the perfect fit for this role. Be sure to mention specific skills and experiences that relate to the job description. We appreciate a personal touch, so let your personality come through!
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 it gets into the right hands. Plus, it shows us you're keen to join our team at StudySmarter!
How to prepare for a job interview at Oliver Bernard
✨Know Your ML Fundamentals
Brush up on your machine learning fundamentals, especially around recommendation and ranking systems. Be ready to discuss algorithms you've used, their pros and cons, and how they can be applied in real-world scenarios.
✨Showcase Your Projects
Prepare to talk about specific projects where you've implemented ML solutions. Highlight your role, the challenges you faced, and the impact of your work. This will demonstrate your hands-on experience and ownership in previous roles.
✨Understand the Company’s Product
Research the company’s platform and its current personalisation features. Think about how you could enhance their recommendation systems and be ready to share your ideas during the interview. This shows your enthusiasm and initiative.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, the tech stack they use, and their future plans for scaling. This not only shows your interest but also helps you gauge if the company is the right fit for you.