Applied Science Intern Computer Vision Amazon jobs at Amazon in Australia, Melbourne

** Join Our Innovative Computer Vision Team at Amazon, Australia **As a member of our international Machine Learning group, you will work closely with other senior scientists in developing generative AI solutions that leverage vast amounts of Amazon data and advanced cloud computing resources.Key job responsibilities
- Communicate clearly within the team to understand and align on scope and requirements

- Experience implementing algorithms using both toolkits and self-developed code
- Experience researching about machine learning, deep learning, NLP, computer vision, data science
- Experience applying theoretical models in an applied environment

As a Senior Applied Scientist in our international Machine Learning team, you will spearhead the design and development of advanced generative models (image, video, and 3D) in computer vision that will enhance shopping experience of our customers. You will partner directly with senior stakeholders to better understand business problems, dissect, design and sometimes build prototypes. You will lead and encourage productive scientific discussions to identify the most effective scientific methodologies.Key job responsibilities
- Lead the scientific development of scalable computer vision solutions to revolutionise our catalog's media content.
- Mentor and guide junior scientists and interns, fostering a culture of innovation and continuous learning.- Drive technical decision-making and set the direction for building future AI models.

- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- 4+ years of building machine learning models for business application experience
- Experience programming in Java, C++, Python or related language
- Have at least 5 publications on top-tier conferences, such as CVPR, ICCV, ECCV or NeurIPS.

- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
- Experience in mentoring PhD students or managing a team of scientists.

What will you do? You will lead a multidisciplinary team to develop solutions across multiple programs working with scientist customers collect, clean, and evaluate data used for AI model training. You will lead the development process and have end-to-end ownership of distributed backend systems as well as front-end tools for human-in-the loop data collection.Key job responsibilities
* Drive architectural changes and designs for the team to scale the AGI-DS planning, routing and execution systems to cater to multiple channels, customer types and workflow types.
* Keep your technical skills current to contribute to architecture and design discussions. Lead your team to evolve and scale our service architecture.
* Drive continual improvements: Set and iteratively improve team processes and mechanisms to make sure the right things get prioritized and work gets done efficiently.A day in the life
A mix of helping the team design systems for building and managing training data, working with the team to deep dive into data quality issues, working with stakeholders to understand their requirements, improving efficiency in our software development processes, career coaching and mentorship, communicating status updates to leadership about progress and challenges, and collaborating with sister teams.

- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team

- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent

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- Present your research findings to both technical and non-technical audiences

- 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

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 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 Computer Vision and Machine Learning- Present your research findings to both technical and non-technical audiencesKey Opportunities:- Access cutting-edge tools and hardware (large GPU clusters)
- Address challenges at an unparalleled scale
- Become a disruptor, innovator, and problem solver in the field of computer vision- Opportunities to become an FTE after the internship

- Currently enrolled in a PhD program in Computer Science, Electrical Engineering, Mathematics, or related field, with specialization in Computer Vision or Machine Learning
- Experience in computer vision or related fields
- Strong programming skills (Python preferred)

Key job responsibilities
- Act as a thought leader sharing best practices through forums such as AWS blogs, whitepapers, reference architectures and public-speaking events such as AWS Summit, AWS re: Invent, etc.A day in the life
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Work/Life Balance

- 7+ years design/implementation/consulting experience of distributed applications
- 5+ years management of technical, customer facing resources
- 5+ years of experience building integrations across WFM, CRM, and contact center solutions or experience with communications protocols and APIs such as WebRTC and SIP or similar CCaaS technology

** Join Our Innovative Computer Vision Team at Amazon, Australia **As a member of our international Machine Learning group, you will play a key role in developing generative AI solutions that leverage vast amounts of Amazon data and advanced cloud computing resources.Key job responsibilities- Develop scalable machine learning and computer vision solutions to revamp the media block of our catalog
- Communicate clearly with business stakeholders to understand and align on requirements- Mentor interns and junior scientists

- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming or scripting language like Python, Java, C or C++
- Have publications on top-tier conferences, such as CVPR, ICCV, ECCV or NeurIPS
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning

- Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms
- 5+ years of building machine learning models or developing algorithms for business application experience
- Experience using Unix/Linux
- Experience with popular deep learning frameworks such as MxNet and Tensor Flow