The latest news and research from Amazon’s science community. #AmazonScience
Seattle, Washington
Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Follow us on LinkedIn and visit our website to get a deep dive on innovation at Amazon, and explore the many ways you can engage with our scientific community. #AmazonScience
On-site · Vancouver
Design and deploy agentic AI systems, retrieval pipelines, and reinforcement learning approaches that detect signals, make decisions, and take action across Alexa products. Build rigorous evaluation and experimentation frameworks, prototype customer-facing AI features, and communicate findings that guide technical architecture and product strategy.
On-site · Vancouver
Develop and train personalized, multimodal language and ranking models for Canadian shopping, and evaluate their performance through offline analysis and online experiments. Define the Canada-focused science strategy, investigate ranking gaps and trade-offs, and collaborate with search, product, engineering, and analytics teams to improve customer outcomes.
On-site · Vancouver
Analyze complex data and apply statistical and machine learning methods to identify patterns, diagnose anomalies, and inform product and engineering decisions. Build scalable data pipelines and analytical frameworks, communicate insights through recommendations and visualizations, and collaborate with cross-functional partners.
On-site · Toronto
Develop, evaluate, and productionize machine learning and deep learning models that provide insights and recommendations for advertising media planning and measurement. Collaborate with scientists, engineers, and product managers to deliver scalable solutions, communicate findings, publish research, and mentor junior scientists.
On-site · Vancouver
Develop and evaluate personalized, multimodal language and ranking models for Canadian shopping, including training models on shopping, reasoning, and localization data. Define the science strategy, analyze Canada-specific quality gaps and trade-offs, lead experiments, and partner with search, product, engineering, and data teams to improve customer outcomes.
On-site · Vancouver
Analyze complex data, develop statistical and modeling approaches, and deliver insights that guide product and engineering decisions and improve Alexa customer experiences. Build scalable data pipelines and analytical frameworks, communicate recommendations through visualizations and presentations, and collaborate with cross-functional teams.
On-site · Vancouver
Research, develop, and deploy on-device AI for communication, including local and cloud inference arbitration, model compression, and inference optimization for NPUs and mobile GPUs. Build privacy-first personalization and edge communication intelligence, and collaborate with hardware, systems, and product teams to bring research advances into production features.
On-site · Toronto
Design, develop, evaluate, deploy, and update data-driven computer vision models, while researching and implementing state-of-the-art computer vision and Vision Language Model algorithms. Collaborate with product and engineering teams to build features for Ring devices and influence technology, data, algorithm, sensor, and system design decisions.
On-site · Vancouver
Design and deliver the permissions language, formal semantics, and authorization systems for AWS's data catalog, ensuring policies are correct, explainable, efficient, and preserve customer access boundaries as data and schemas evolve. Lead complex scientific work, build cross-team consensus, improve system efficiency and consistency, and advance research through publications and talks.
On-site · Vancouver
Design and formally specify expressive, explainable, and testable permissions models for AWS's data catalog, and ensure authorization decisions remain correct, efficient, and aligned with customer intent as policies and resources change. Lead complex scientific components, build cross-team consensus, influence strategy, and advance research in data security, governance, programming languages, and automated reasoning.
On-site · Vancouver
Design and deploy agentic AI systems, retrieval pipelines, and reinforcement learning approaches that detect signals, make decisions, and take action across Alexa products. Develop rigorous evaluation and benchmarking methods, prototype customer-facing AI features, and run experiments that inform product and architecture decisions.
On-site · Vancouver
Own the scientific direction and roadmap for a Smart Home workstream, framing research problems, developing models, and validating their customer and business impact. Partner with engineering and product to bring reliable, cost-effective models into production, influence technical direction, mentor scientists, and contribute to scientific publications and patents.
On-site · Vancouver
Design and develop end-to-end science systems, create technical roadmaps, and drive production-level projects supporting Amazon Science. Collaborate with scientists, interns, and cross-functional teams to develop solutions and deploy them into production.
