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- Tasks: Apply machine learning techniques to digital identity verification and build production models.
- Company: Leading identity technology firm in Greater London with a focus on innovation.
- Benefits: Flexible working, performance-based bonus, private medical insurance, and cycle-to-work scheme.
- Other info: Dynamic work environment with opportunities for growth and development.
- Why this job: Join a cutting-edge team and make a real impact in digital identity technology.
- Qualifications: PhD in a related field and strong Python skills required.
The predicted salary is between 36000 - 60000 £ per year.
A leading identity technology firm in Greater London is seeking a Machine Learning Engineer to work on projects in Computer Vision, Machine Learning, and Deep Learning. You will apply machine learning techniques to digital identity verification and build models for production deployment.
The ideal candidate holds a PhD in a related field and possesses strong Python skills.
The company offers flexible working, a performance-based bonus, and numerous benefits including private medical insurance and a cycle-to-work scheme.
Junior Research Scientist — ML/CV for Digital Identity employer: Yoti
Contact Detail:
Yoti Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Junior Research Scientist — ML/CV for Digital Identity
✨Tip Number 1
Network like a pro! Reach out to professionals in the field of Machine Learning and Computer Vision on platforms like LinkedIn. A friendly message can go a long way, and you never know who might have a lead on that perfect job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects in ML and CV. Whether it's GitHub repos or a personal website, having tangible evidence of your work can really impress potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your Python skills and understanding the latest trends in digital identity verification. We recommend doing mock interviews with friends or using online platforms to get comfortable with common questions.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Junior Research Scientist — ML/CV for Digital Identity
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in Machine Learning and Computer Vision. We want to see how your skills align with the projects you'll be working on, so don’t hold back on showcasing your Python prowess!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about digital identity verification and how your background makes you a perfect fit for our team. Let us know what excites you about the role!
Showcase Your Projects: If you've worked on any cool projects related to ML or CV, make sure to mention them! We love seeing practical applications of your skills, so include links to your GitHub or any relevant portfolios.
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’s super easy – just follow the prompts!
How to prepare for a job interview at Yoti
✨Know Your ML and CV Basics
Make sure you brush up on your machine learning and computer vision fundamentals. Be ready to discuss key concepts, algorithms, and their applications in digital identity verification. This will show that you’re not just familiar with the theory but can also apply it practically.
✨Showcase Your Python Skills
Since strong Python skills are a must for this role, prepare to demonstrate your coding abilities. You might be asked to solve a problem or explain your previous projects. Practise coding challenges related to ML and CV to boost your confidence.
✨Prepare for Technical Questions
Expect technical questions that dive deep into your knowledge of machine learning models and their deployment. Think about how you would approach real-world problems in digital identity verification and be ready to discuss your thought process.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the team’s current projects, the technologies they use, or how they measure success in their ML initiatives. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.