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- Tasks: Develop cutting-edge recommendation algorithms and collaborate with data and engineering teams.
- Company: A dynamic, data-driven platform company based in the UK.
- Benefits: Flexible hybrid work model with part-time office attendance in London.
- Why this job: Join a growing team and make an impact with advanced machine learning techniques.
- Qualifications: Strong Python skills and experience in deploying recommendation systems.
- Other info: Exciting opportunities for career growth in a fast-paced environment.
The predicted salary is between 36000 - 60000 £ per year.
A growing data-driven platform company in the UK is seeking an Associate Director in Data & AI Recruitment. You will develop recommendation algorithms, work with advanced machine learning techniques, and collaborate closely with engineering and data teams.
Ideal candidates have robust Python skills and experience in deploying recommendation systems. This hybrid role allows for flexibility with part-time office attendance in London.
Hybrid ML Engineer — Real-Time Recommender Systems in England employer: Xcede
Contact Detail:
Xcede Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Hybrid ML Engineer — Real-Time Recommender Systems in England
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people 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 involving recommendation algorithms and machine learning. 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 Python skills and understanding the latest trends in real-time recommender systems. Practice common interview questions and be ready to discuss your past experiences in detail.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team directly.
We think you need these skills to ace Hybrid ML Engineer — Real-Time Recommender Systems in England
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your Python expertise in your application. We want to see how you've used it in real projects, especially when it comes to developing recommendation algorithms.
Tailor Your Experience: When writing your application, focus on your experience with machine learning techniques and deploying recommendation systems. We love seeing how your background aligns with what we do at StudySmarter!
Be Clear and Concise: Keep your application clear and to the point. We appreciate straightforward communication, so make sure your skills and experiences shine without unnecessary fluff.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity.
How to prepare for a job interview at Xcede
✨Know Your Algorithms
Brush up on your knowledge of recommendation algorithms and machine learning techniques. Be ready to discuss how you've implemented these in past projects, as well as the challenges you faced and how you overcame them.
✨Showcase Your Python Skills
Since robust Python skills are a must, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice coding exercises related to data manipulation and algorithm implementation.
✨Collaborate Like a Pro
This role involves working closely with engineering and data teams, so be prepared to discuss your experience in collaborative environments. Share examples of successful teamwork and how you’ve contributed to cross-functional projects.
✨Embrace the Hybrid Model
As this is a hybrid role, express your flexibility and willingness to adapt to both remote and in-office work. Highlight any previous experiences that showcase your ability to thrive in a hybrid work environment.
