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- Tasks: Lead the development of cutting-edge recommender systems and optimise machine learning models.
- Company: Join Cleo, a forward-thinking tech company in Greater London.
- Benefits: Enjoy a competitive salary, flexible work options, and generous benefits like private medical insurance.
- Other info: Great opportunity for career growth in a dynamic and innovative environment.
- Why this job: Make a real impact in personalisation technology while collaborating with diverse teams.
- Qualifications: Advanced degree in a quantitative field and experience in data science required.
The predicted salary is between 70000 - 90000 £ per year.
Cleo is looking for a Senior Machine Learning Engineer to lead technical work within their Machine Learning Growth Personalisation team in Greater London. The role involves building and optimizing recommender systems, developing models for production, and collaborating with cross-functional teams.
Candidates should have experience in data science, excellent communication skills, and an advanced degree in a quantitative discipline.
The position offers a competitive salary, flexible work arrangements, and generous benefits including a pension and private medical insurance.
Lead Personalisation ML Engineer — Recommenders & Bandits employer: cleo
Contact Detail:
cleo Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Personalisation ML Engineer — Recommenders & Bandits
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Cleo or similar companies. A friendly chat can sometimes lead to opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your work on recommender systems and machine learning models. This will give you an edge and demonstrate your expertise beyond just your CV.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as communication is key when collaborating with cross-functional teams.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Lead Personalisation ML Engineer — Recommenders & Bandits
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in building and optimising recommender systems. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about machine learning and how you can contribute to our team. We love hearing about your journey and what drives you.
Showcase Your Communication Skills: Since collaboration is key in this role, make sure to highlight your communication skills in your application. We value clear and effective communication, so share examples of how you've worked with cross-functional teams.
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at cleo
✨Know Your Stuff
Make sure you brush up on your machine learning concepts, especially around recommender systems and bandit algorithms. Be ready to discuss your past projects in detail, showcasing your technical skills and how you've optimised models for production.
✨Showcase Collaboration Skills
Since the role involves working with cross-functional teams, prepare examples of how you've successfully collaborated with others in the past. Highlight your communication skills and how you’ve navigated challenges in team settings.
✨Ask Insightful Questions
Prepare thoughtful questions about Cleo's current projects and future goals in personalisation. This shows your genuine interest in the role and helps you understand how you can contribute to their success.
✨Be Ready for Technical Challenges
Expect some technical questions or coding challenges during the interview. Practise common algorithms and data structures, and be prepared to explain your thought process clearly as you solve problems.