Updating Results

Applied Scientist Intern - Machine Learning, Recommender Systems (Rolling Intake)

Location details

On-site

  • Australia

    Australia

    • Australian Capital Territory

      Canberra

    • New South Wales

      Sydney

    • Queensland

      Brisbane

    • Victoria

      Melbourne

    • Western Australia

      Perth

Location

Canberra, Sydney, Brisbane

Closing in 2 weeks

Opportunity details

  • Opportunity typeInternship, Clerkship or Placement
  • SalaryAUD 120000 / Year
  • Number of vacancies3 vacancies
  • Application open dateApply by 28 Feb 2025
  • Start dateStart date Ongoing

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

Please note that recruitment for Amazon’s Applied Science internship takes place all 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 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.

Work rights

The opportunity is available to applicants in any of the following categories.

Work light flag
Australia
Australian CitizenAustralian Permanent ResidentInternational Student/Graduate VisaAustralian Work Visa (All Other)

Qualifications & other requirements

You should have or be completing the following to apply for this opportunity.

Degree or Certificate
Qualification level
Qualification level
Doctorate (PhD) or higher
Study field
Study field (any)

Hiring criteria

  • Experience requirementNo experience required
  • Working rights
    Australian Citizen
  • Study fields
    Engineering & Mathematics
  • Degree typesDoctorate (PhD) or higher
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Reviews

user
Trainee
Sydney
5 months ago

Decommission severs around different data centres

user
Intern
Sydney
a year ago

As a Brand Specialist Intern, there are two components to the intern program: your designated intern project and the Amazon Vendor Services (AVS) task list. The intern program is designed for you to have ownership by working on a specific problem project whilst giving you a taste of what it's like to be a working Brand Specialist (ie. vendor management, instock management, etc.).

user
Graduate
Sydney
a year ago

Engaging customers, trying to identify their problems and connect them with the village of Amazonians that have the expertise to solve those problems. This means calling customers, hosting meetings, preparing experts with customer information for those meetings and collating compelling narratives around a problem or solution from our 1000's of customer references. It also means connecting with the Amazon Partner Network - learning about our partners, their offerings and other opportunities or relationships with our customers.

Show all reviews

About the employer

Amazon logo

Amazon AU

Rating

4.3

Number of employees

> 100,000 employees

Industries

Technology

Amazon's mission is to be Earth's most customer-centric company. Our actions, goals, and inventions begin and end with the customer's top of mind.

Pros and cons of working at Amazon AU

Pros

  • I enjoy the ownership of my intern project the most at Amazon... There's a large component of fulfilment I receive whenever I find pain points and strategise ways to solve them.

  • Everyone is super friendly and genuinely interested in the work I was doing. Everyone is happy to help and provide valuable feedback, insight, or advice.

  • The decom team is a very supportive and easy-going environment. We have laughs and talk about anything, but when work needs to be done, we collectively lock in and get the work done.

  • The work hours are really flexible. There is no formal logging of hours, and working from home is also an option.

  • The office is located in Town Hall, so it's super convenient... The working spaces are close to huge windows and have lots of plants. There are games rooms with virtual reality headsets, Nintendo Switches, and more.

Cons

    • Since Amazon is a big global company, it does take some time for requested data to be received, especially when dealing with different international time zones.

    • AVS is incredibly results-oriented, which has resulted in some churn over recent periods as people have been unable to deliver results in a way that would allow them to pass their probation period.

    • The interview process was very intense with three rounds, making it difficult but rewarding.

    • Like most jobs, I'd like higher pay but cannot complain.

    • Due to the size of the company and global time zones, responses to urgent queries may be delayed.