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Applied Science Intern (Machine Learning, Recommender Systems)

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Amazon Pforzheim GmbH

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Location:
Australia , Sydney ▼

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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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 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.

Job Responsibility:

  • 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

Requirements:

  • Are enrolled in a PhD in computer science, machine learning, engineering, or related fields
  • Experience with video and image processing and compression algorithms and standards, computer vision and/or machine learning
  • Strong programming skills (Python preferred)

Nice to have:

  • Experience researching about machine learning, deep learning, NLP, computer vision, data science
  • Publications in top-tier conferences such as CVPR, ICCV, NeurIPS, ICML, ICLR, ECCV, etc. Please list these publications on your resume.
What we offer:
  • 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

Additional Information:

Job Posted:
May 05, 2026

Employment Type:
Fulltime
Work Type:
On-site work
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