At a Glance
- Tasks: Design and develop AI systems that make a real-world impact.
- Company: Join Amazon, a leader in innovation and technology.
- Benefits: Competitive salary, mentorship, networking opportunities, and potential for publication.
- Other info: Internships last 3-6 months with various start dates; no remote options available.
- Why this job: Shape the future of AI while working on exciting projects with top scientists.
- Qualifications: PhD enrolment in relevant fields and programming skills in Java, C++, or Python.
The predicted salary is between 22500 - 27500 £ per year.
Описание
We're building systems that turn research into real-world impact — ensuring flawless streaming for millions of Prime Video customers, shaping the future of AI-driven shopping with Rufus, advancing speech generation and conversational AI, optimizing large-scale infrastructure through intelligent observability, and transforming how people and jobs find each other.
If this sounds interesting to you then we have a range of opportunities for you to explore.
Задачи
As an Applied Science Intern, you will own the design and development of end-to-end systems.
You'll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science.
You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production.
You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon's customer focused culture.
The ideal intern should have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems.
You'll spend your first weeks scoping your project with your mentor, then own the research and implementation end-to-end.
Your work could involve building computer vision models that detect quality issues across Prime Video's content library, developing multimodal AI solutions that power Amazon's shopping assistant Rufus, creating automated reasoning tools that verify distributed systems at scale, engineering intelligent observability frameworks for large-scale infrastructure, or advancing recommendation models that connect people with the right jobs — depending on the team you're matched with.
- Требования
- Are enrolled in a Ph D in computer science, machine learning, engineering, or related fields
- Experience programming in Java, C++, Python or related language
- Speak, write, and read fluently in English
- Будет плюсом: Have publications at top-tier peer-reviewed conferences or journals; Experience in solving business problems through machine learning, data mining and statistical algorithms; Experience in designing experiments and statistical analysis of results; Experience implementing algorithms using toolkits and self-developed code
- Условия
- All of our internships offer a competitive salary
- Interns are paired with an experienced manager and mentor(s)
- Interns get invited to different intern program or office events
- Interns can build their professional and personal network with other Amazon Scientists
- Interns can potentially publish work at top tier conferences
- Start dates are available throughout the year for durations of between 3–6 months.
- Please note, each team has different start date and duration preferences — your recruiter will confirm the preferences of the team you're matched with prior to interviewing.
- Please note we do not offer remote internships.
Applied scientist in AI in London employer: Amazon Inc.
At Amazon Development Centre in Edinburgh, we are committed to fostering a collaborative and inclusive work culture that empowers our employees to innovate and excel. As an Applied Scientist in our Intelligent Talent Acquisition team, you will have the opportunity to work on cutting-edge machine learning technologies that directly impact recruitment processes, while benefiting from mentorship and professional growth opportunities. Join us to make a meaningful difference in how talent is acquired globally, all within a vibrant city known for its rich history and dynamic tech scene.
StudySmarter Expert Advice🤫
We think this is how you could land Applied scientist in AI in London
✨Join Data-Science Meetups
Get yourself along to local data-science meetups or workshops. They're goldmines for networking, and you'll learn from industry pros who might just point you in the direction of internships. Plus, discussing the latest trends with like-minded individuals can really amp up your game.
✨Utilise University Career Services
Check in with your uni's career services since they often have connections with companies looking for interns. They might even organise information sessions with firms, which can be a great chance for you to learn more about potential internships and make some key contacts.
✨Show Off Your Stuff on GitHub
If you're into data science, having a GitHub profile with your projects is essential. Make sure your portfolio is public and showcases your best work! Recruiters love to see your coding skills and problem-solving approach, and it’s a brilliant way to stand out.
✨Apply Directly on Our Website
Don’t forget to check out the internships listed on our site! It's always a good idea to apply directly through our website because it makes your application easier for our team to find, and you might just catch the hiring manager’s eye by showcasing exactly what you're passionate about in data science.
We think you need these skills to ace Applied scientist in AI in London
Some tips for your application 🫡
Show Off Your Technical Skills:For a data science internship, we want to see those analytical skills shine! List your programming languages, like Python or R, and make sure to highlight any relevant projects or courses you've completed. If you've dabbled with tools like Pandas, NumPy, or machine learning algorithms, don’t hold back – include those in your CV!
Share Your Curiosity in Your Cover Letter:As an intern, your motivation and eagerness to learn are key! In your cover letter, talk about specific data science concepts that excite you and how this internship at Amazon Inc. will help you grow. Share what you hope to achieve and how you plan to tackle real-world data problems - we love enthusiasm!
Include Any Relevant Certifications:If you've earned any certifications, such as from Coursera or DataCamp, make sure to include these in your application. They show us that you're proactive and committed to expanding your data science skillset. This could make a real difference in how we assess your application!
Keep It Relevant and Concise:Remember, as an intern, you don’t need to have decades of experience. Focus on showcasing relevant coursework, personal projects, or even related volunteer work in data science. Keep your CV and cover letter concise but impactful – we appreciate clear and straightforward communication!
How to prepare for a job interview at Amazon Inc.
✨Brush Up on Your Coding Skills
As a data science intern, you might get grilled on your programming skills. Expect to tackle some coding challenges using languages like Python or R. We recommend practising basic algorithms or data manipulation tasks so you can show off your tech skills with confidence.
✨Show Off Your Projects
Prepare to discuss any projects you’ve done, whether in your studies or on your own time. Having a strong portfolio of data analyses or machine learning models will really set you apart. We can use platforms like GitHub to showcase your work to impress Amazon Inc..
✨Know Your Stats and ML Basics
Brush up on your statistics and machine learning concepts because interviewers love to dig into this! Be ready to explain your understanding of algorithms or how you would approach a given data problem. This will highlight your theoretical background alongside your practical skills.
✨Be Eager to Learn and Adapt
Internships are all about potential and growth. Make sure you convey your eagerness to learn and adapt to new tools or methodologies. Show Amazon Inc. that you’re not just looking for experience, but that you're keen to contribute and grow within the team.
