2025 Applied Science Intern (Machine Learning, Recommender Systems), Amazon International Machine Learning

This is a 2025 Applied Science Intern (Machine Learning, Recommender Systems), Amazon International Machine Learning role with Amazon based in Brisbane, QLD, AU

• Amazon --
  
  

Role Seniority - intern

More about the 2025 Applied Science Intern (Machine Learning, Recommender Systems), Amazon International Machine Learning role at Amazon

Description

Are you excited about leveraging state-of-the-art Deep Learning, Recommender Systems, Information Retrieval, Natural Language Processing algorithms on large datasets to solve real-world problems?

As an Applied Scientist Intern, you will be working in the closest Amazon offices to you (Sydney, Melbourne, Adelaide, Brisbane) in a fast-paced, cross-disciplinary team of experienced R&D scientists. You will take on complex problems, work on solutions that leverage existing academic and industrial research, and utilize your own out-of-the-box pragmatic thinking. In addition to coming up with novel solutions and prototypes, you may even deliver these to production in customer facing products.

Key job responsibilities

Develop novel solutions and build prototypes

Work on complex problems in Machine Learning and Information Retrieval

Contribute to research that could significantly impact Amazon operations

Collaborate with a diverse team of experts in a fast-paced environment

Collaborate with scientists on writing and submitting papers to top conferences, e.g. NeurIPS, ICML, KDD, SIGIR

Present your research findings to both technical and non-technical audiences

Key Opportunities

Work in a team of ML scientists to solve recommender systems problems at the scale of Amazon

Access to Amazon services and hardware

Become a disruptor, innovator, and problem solver in the field of information retrieval and recommender systems

Potentially deliver solutions to production in customer-facing applications

Opportunities to be hired full-time after the internship

Join us in shaping the future of AI at Amazon. Apply now and turn your research into real-world solutions!

Basic Qualifications

Currently enrolled in a PhD program in Computer Science, Electrical Engineering, Mathematics, or related field, with specialization in Information Retrieval, Recommender Systems, or Machine Learning

Strong programming skills, e.g. Python and DL frameworks

Preferred Qualifications

Research experience in Deep Learning, Recommender Systems, Information Retrieval, or broader Machine Learning.

Publications in top-tier conferences, e.g. NeurIPS, ICML, ICLR, KDD, SIGIR, RecSys

Experience with handling large datasets and distributed computing, e.g. Spark

Program Details

Recruitment occurs year-round

Internships start monthly and last 6 months

Have a question?

Please click on the below link to view our FAQs document: https://amazonexteu.qualtrics.com/CP/File.php?F=F_ctP17e4M4BpNzi6

But if you have any other questions not answered in anzcampus@amazon.com.au

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Acknowledgement Of Country

In the spirit of reconciliation Amazon acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.

IDE Statement

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Company - Amazon Support Services PtyLtd

Job ID: A2794872

Before we jump into the responsibilities of the role. No matter what you come in knowing, you’ll be learning new things all the time and the Amazon team will be there to support your growth.

🟢 Please consider applying even if you don't meet 100% of what’s outlined 🟢

Key Responsibilities

• 💡 Developing novel solutions and building prototypes
• 🔧 Working on complex problems in Machine Learning and Information Retrieval
• 🤝 Collaborating with a diverse team of experts
  
  

Key Strengths

• 🧠 Deep Learning
• 🔍 Recommender Systems
• 📊 Information Retrieval
• 💬 Natural Language Processing
• 🌐 Distributed Computing
• 📄 Research Publication
  
  

Why Amazon is partnering with Hatch on this role. Hatch exists to level the playing field for people as they discover a career that’s right for them. So when you apply you have the chance to show more than just your resume.

A Final Note: This is a role with Amazon not with Hatch.

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