2027 Applied Science Intern (Computer Vision), Amazon International Machine Learning
Amazon
Full-time
other-general
Location
Melbourne, Australia, Australia
Posted
June 27, 2026
Job Description
Description
Are you excited about leveraging state-of-the-art Computer Vision algorithms and large datasets to solve real-world problems? Join Amazon as an Applied Scientist Intern and be at the forefront of AI innovation!
As an Applied Scientist Intern, you'll work in a fast-paced, cross-disciplinary team of pioneering researchers. You'll tackle complex problems, developing solutions that either build on existing academic and industrial research or stem from your own innovative thinking. Your work may even find its way into customer-facing products, making a real-world impact.
Please note: This internship is a duration of 6 months full time with a start date in Jan-March 2027.
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 Computer Vision and Machin...
Are you excited about leveraging state-of-the-art Computer Vision algorithms and large datasets to solve real-world problems? Join Amazon as an Applied Scientist Intern and be at the forefront of AI innovation!
As an Applied Scientist Intern, you'll work in a fast-paced, cross-disciplinary team of pioneering researchers. You'll tackle complex problems, developing solutions that either build on existing academic and industrial research or stem from your own innovative thinking. Your work may even find its way into customer-facing products, making a real-world impact.
Please note: This internship is a duration of 6 months full time with a start date in Jan-March 2027.
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 Computer Vision and Machin...