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- Tasks: Design and scale production-grade ML systems for personalised rewards.
- Company: Join a high-growth, profitable tech company in London.
- Benefits: Competitive salary, flexible work options, and growth opportunities.
- Other info: Be part of a dynamic team shaping the future of technology.
- Why this job: Make a real impact on the company's technical direction with your expertise.
- Qualifications: Strong background in statistical methods and machine learning.
The predicted salary is between 60000 - 80000 £ per year.
Dex is looking for a specialist to join a high-growth, profitable technology company in London. This role focuses on designing and scaling production-grade ML systems while optimizing personalized reward mechanisms. Candidates should have a strong background in statistical methods and machine learning, particularly in high-scale environments. This position offers an impactful opportunity within a team that plays a crucial role in shaping the company's technical direction.
Staff ML Engineer (Python) — Real-Time pLTV & Growth employer: Dex
Contact Detail:
Dex Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff ML Engineer (Python) — Real-Time pLTV & Growth
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working at Dex or similar companies. A friendly chat can open doors and give you insights that might just land you an interview.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those involving real-time systems or personalised reward mechanisms. This will help us see your practical experience and how you can contribute to our team.
✨Tip Number 3
Prepare for technical interviews by brushing up on your statistical methods and machine learning concepts. We want to see how you think and solve problems, so practice coding challenges and system design questions relevant to high-scale environments.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows us you’re genuinely interested in joining our team at Dex and making an impact in the tech world.
We think you need these skills to ace Staff ML Engineer (Python) — Real-Time pLTV & Growth
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with machine learning and statistical methods. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements in high-scale environments!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the role and how you can contribute to our team. We love seeing genuine enthusiasm and a clear understanding of what we do.
Showcase Relevant Projects: If you've worked on any projects related to ML systems or personalized reward mechanisms, make sure to mention them. We’re keen to see real-world applications of your skills, so include links or descriptions that highlight your impact.
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 you’re serious about joining our team!
How to prepare for a job interview at Dex
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts, especially those related to statistical methods and high-scale environments. Be ready to discuss your past projects and how you've designed or scaled ML systems in production.
✨Showcase Your Python Skills
Since this role is focused on Python, be prepared to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice coding challenges that involve ML algorithms and data manipulation.
✨Understand the Company’s Vision
Research Dex and understand their approach to personalized reward mechanisms. Being able to articulate how your skills align with their goals will show that you're genuinely interested in the role and the company.
✨Prepare Questions
Have a few insightful questions ready to ask at the end of the interview. This could be about their current ML projects or how they envision the growth of their technology. It shows you're engaged and thinking critically about the role.