Une candidature complète en une minute
Un CV et une lettre de motivation personnalisés, prêts à envoyer.
Amazon Inc. is seeking an Applied Scientist II for the Cross Border Science & Analytics team in Bengaluru.
You will design, develop, and deploy ML models to improve cross-border shopping experiences for Amazon customers worldwide, with end-to-end ownership and significant autonomy. You will work on challenging problems across search, pricing, recommendations, and language understanding, publishing research and collaborating with world-class scientists and engineers.
The Cross-Border (XB) Science & Analytics team is at the heart of Amazon's international marketplace expansion, powering science-driven solutions that enable customers across 20+ countries to discover and purchase products seamlessly across borders. Our work directly impacts millions in annualized business value through ML models, algorithms, and data-driven systems that solve some of Amazon's most complex cross-border challenges.
We are a lean, high-impact team of scientists working across various programs spanning search ranking, demand forecasting, pricing optimization, product recommendations, language understanding, and generative AI. We partner closely with product, engineering, and business teams across Amazon's global retail organization to take science from ideation to production at scale.
We are looking for a passionate and technically strong Applied Scientist to join our team. In this role, you will design, develop, and deploy machine learning models and algorithms that directly improve the cross-border shopping experience for millions of Amazon customers worldwide. You will work on challenging, ambiguous problems—from improving search relevance across languages to building ML-powered pricing and recommendation systems—with significant autonomy and end-to-end ownership.
This is a hands‑on, high‑visibility role. You will publish your research internally and externally, collaborate with world‑class scientists and engineers, and see your work go live across Amazon's global marketplaces.
Analyze large-scale datasets to identify patterns, formulate hypotheses, and design experiments
Develop and iterate on ML models (deep learning, NLP, ranking, causal inference) to improve cross‑border product discovery, relevance, and conversion
Design and run A/B experiments on live traffic to measure model impact against business and customer metrics
Write production‑quality code (Python, Java/Scala) and work with SDEs to deploy models into real‑time and batch inference pipelines
Build end‑to‑end ML pipelines—including data ingestion and feature engineering to training, evaluation, and online serving
Own model monitoring, performance debugging, and iterative improvements post‑launch
Participate in weekly science syncs, design reviews, and cross‑functional stand‑ups with product managers, engineers, and business stakeholders
Translate business problems into well‑defined science problems, and communicate results and trade‑offs to both technical and non‑technical audiences
Contribute to technical documentation—architecture wikis, experiment write‑ups, and model cards
Present at internal ML paper reading sessions and science forums
Stay current with state‑of‑the‑art research (NeurIPS, ICLR, ACL, KDD) and bring new ideas to the team
Mentor junior scientists and interns; participate in hiring interviews and debriefs
Publish findings in top‑tier venues and file patents where applicable
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.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Veterans, military spouses, and people with disabilities are encouraged to apply.