At a Glance
- Tasks: Design and build cutting-edge recommendation systems to transform hiring at Amazon.
- Company: Join Amazon Science in Edinburgh, a leader in tech innovation.
- Benefits: Competitive salary, diverse work culture, and opportunities for professional growth.
- Other info: Collaborate with experts across disciplines in a dynamic environment.
- Why this job: Make a real impact on recruitment processes and help foster diversity.
- Qualifications: PhD in computer science or related field, with machine learning experience.
The predicted salary is between 60000 - 80000 £ per year.
Amazon Science in Edinburgh is seeking a Machine Learning Engineer to design and build recommendation systems that transform the hiring experience. You will implement models that ensure high performance and reliability, and collaborate closely with experts across various disciplines.
The ideal candidate holds a PhD in computer science or a related field, has experience with machine learning and programming, and is fluent in English. Join us to help Amazon enhance its recruitment processes and foster a diverse workforce.
Applied ML Scientist, Talent Acquisition Recommender employer: Amazon Science
Amazon Science in Edinburgh offers an exceptional work environment where innovation meets collaboration. As an Applied ML Scientist, you will not only contribute to cutting-edge technology but also enjoy a culture that prioritises employee growth and diversity. With access to extensive resources and opportunities for professional development, Amazon is committed to fostering a rewarding career path in the heart of Scotland's vibrant tech community.
StudySmarter Expert Advice🤫
We think this is how you could land Applied ML Scientist, Talent Acquisition Recommender
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Amazon. 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 machine learning projects. This is your chance to demonstrate your expertise and creativity, making you stand out from the crowd.
✨Tip Number 3
Prepare for the technical interview! Brush up on your algorithms and data structures, and be ready to discuss your past projects. We want to see how you think and solve problems, so practice makes perfect!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in joining the team at Amazon Science.
We think you need these skills to ace Applied ML Scientist, Talent Acquisition Recommender
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Applied ML Scientist role. Highlight your experience with machine learning and programming, and don’t forget to mention any relevant projects or research that align with the job description.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about transforming the hiring experience through recommendation systems. Show us how your skills and experiences make you the perfect fit for our team.
Showcase Your Collaboration Skills:Since this role involves working closely with experts from various disciplines, be sure to highlight any past experiences where you’ve successfully collaborated with others. We love seeing teamwork in action!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team at Amazon Science!
How to prepare for a job interview at Amazon Science
✨Know Your ML Fundamentals
Brush up on your machine learning concepts, especially those related to recommendation systems. Be ready to discuss algorithms, model evaluation metrics, and any relevant projects you've worked on. This shows you’re not just familiar with the theory but can apply it practically.
✨Showcase Your Programming Skills
Prepare to demonstrate your programming abilities, particularly in languages like Python or R. You might be asked to solve coding problems or explain your code from past projects. Practising common coding challenges can help you feel more confident.
✨Collaborative Mindset
Since the role involves working closely with experts from various disciplines, be prepared to discuss how you’ve successfully collaborated in the past. Share examples that highlight your teamwork skills and how you’ve contributed to a diverse environment.
✨Ask Insightful Questions
Prepare thoughtful questions about Amazon's approach to recruitment and how they leverage machine learning. This not only shows your interest in the role but also helps you gauge if the company culture aligns with your values.
