【Class of 2028／Full-Time】Applied Scientists , Amazon International Stores, Amazon Japan Store Tech

Do you want to see your research directly impact how millions of customers discover, browse, and purchase products on Amazon — across Japan and the globe?

Amazon's Japan Store Tech team owns the science and technology behind cross-border shopping — product discovery, search relevance, personalization, and content experiences spanning dozens of marketplaces. We tackle problems at massive scale: multi-language signals, multi-marketplace data, and region-specific customer behaviors, all served at low latency to millions of daily shoppers.

We're looking for current Bachelor, Master or PhD students with a passion for applied science and machine learning to join us as an Applied Scientist in 2028 to shape the future of customer experiences at scale. For this position, our Japan Store Tech team is looking for students with a specialization in one or more of the following research areas: machine learning, deep learning, natural language processing (NLP), information retrieval, recommender systems, computer vision, large language models (LLMs), generative AI, causal inference, experimentation and A/B testing, optimization, and more!

As an Applied Scientist, you'll develop novel models and algorithms, design and run experiments on live traffic, and own meaningful science contributions end-to-end. You'll also leverage and contribute to GenAI/LLM systems that power both customer-facing experiences and internal development tools.

If you want to kickstart your science career at global scale — solving real customer problems alongside talented scientists and engineers in a collaborative, international environment — this is the place to start.

Selection Communication Begins:

October 5, 2026

Offer Extensions:

December 2026 – March 2027

Key job responsibilities

• Collaborate and communicate effectively with experienced cross-disciplinary Amazonians to design, develop, and deploy innovative machine learning models and scientific solutions that delight our customers, while participating in technical discussions to drive solutions forward.

• Develop and implement scalable machine learning models and algorithms to improve product discovery, search relevance, personalization, or other customer-facing experiences.

• Design and conduct experiments (offline and online) to validate hypotheses and measure the impact of proposed solutions.

• Analyze large-scale datasets to identify patterns, generate insights, and inform model design decisions.

• Leverage and contribute to the development of GenAI and LLM-powered tools to enhance customer experiences and development productivity while staying current with emerging technologies.

• Write clean, maintainable, production-quality code following best practices.

• Communicate research findings effectively through documentation, presentations, and technical papers.

• Work in an agile environment and collaborate closely with software engineers to bring science solutions from prototype to production. Basic qualifications
• Currently enrolled in a Bachelor or Master program in Computer Science, Machine Learning, Statistics, Applied Mathematics, Electrical Engineering, or a related quantitative field.
• Programming experience in one or more of: Python, Java, C++, or equivalent.
• Coursework or research experience in one or more of: machine learning, deep learning, NLP, information retrieval, computer vision, statistics, or optimization.
• Strong foundation in data structures, algorithms, and mathematical/statistical modeling.
• Expected to graduate in 2028 and able to start from either April 1st or October 1st in 2028.

Preferred qualifications

• Publications or submitted papers in top-tier venues (e.g., NeurIPS, ICML, ACL, EMNLP, CVPR, KDD, WWW, RecSys, SIGIR).
• Hands-on experience building and deploying ML models on large-scale datasets.
• Experience with deep learning frameworks (e.g., PyTorch, TensorFlow, JAX).
• Familiarity with large language models, generative AI, or retrieval-augmented generation (RAG).
• Experience designing and analyzing A/B tests or causal inference experiments.
• Strong written and verbal communication skills; ability to present complex technical ideas clearly.
• Experience with cloud computing platforms (e.g., AWS).
• Proficiency in Japanese is a plus but not required; English fluency is required.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.