2025 Applied Science Intern (Machine Learning, Recommender Systems), Amazon International Machine Learning Are you excited about leveraging state-of-the-art Deep Learning, Recommender Systems, Information Retrieval, and 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!
Minimum Requirements: 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 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.
If you have a question, please click on the below link to view our FAQs document: FAQs Document . For any other questions not answered, contact .
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 committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected attributes.
#J-18808-Ljbffr