2026 Applied Science Intern (Machine Learning, Recommender Systems), International Machine Learning
Job 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 based in Amazon's Melbourne office working 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.Please note: This internship is a duration of 6 months full time with a start date in Jan-March 2026.The successful intern is required to be based in Melbourne and relocation allowance will be provided if you are based outside of Melbourne. 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!
Locations
- Australia, VIC, Melbourne, Melbourne, VIC, Australia
Salary
Salary not disclosed
Estimated Salary Rangemedium confidence
60,000 - 90,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Required 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 (degree in a phd program in computer science)
- - Strong programming skills, e.g. Python and DL frameworks (experience)
Preferred Qualifications
- - Research experience in Deep Learning, Recommender Systems, Information Retrieval, or broader Machine Learning. (experience)
- - Publications in top-tier conferences, e.g. NeurIPS, ICML, ICLR, KDD, SIGIR, RecSys (experience)
- - Experience with handling large datasets and distributed computing, e.g. Spark (experience)
- Acknowledgement of country: (experience)
- 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. (experience)
- IDE statement: (experience)
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!
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Tags & Categories
2026 Applied Science Intern (Machine Learning, Recommender Systems), International Machine Learning
Job 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 based in Amazon's Melbourne office working 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.Please note: This internship is a duration of 6 months full time with a start date in Jan-March 2026.The successful intern is required to be based in Melbourne and relocation allowance will be provided if you are based outside of Melbourne. 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!
Locations
- Australia, VIC, Melbourne, Melbourne, VIC, Australia
Salary
Salary not disclosed
Estimated Salary Rangemedium confidence
60,000 - 90,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Required 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 (degree in a phd program in computer science)
- - Strong programming skills, e.g. Python and DL frameworks (experience)
Preferred Qualifications
- - Research experience in Deep Learning, Recommender Systems, Information Retrieval, or broader Machine Learning. (experience)
- - Publications in top-tier conferences, e.g. NeurIPS, ICML, ICLR, KDD, SIGIR, RecSys (experience)
- - Experience with handling large datasets and distributed computing, e.g. Spark (experience)
- Acknowledgement of country: (experience)
- 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. (experience)
- IDE statement: (experience)
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!