Take Earth's most customer-centric company. Mix in hundreds of millions of shoppers spending tens of billions of dollars annually, an exciting opportunity to build next-generation shopping experiences, Amazon’s tremendous computational resources, and our extensive e-Commerce experience. What do you get? The most exciting position in the industry.
About our team:
Our mission is to delight every Amazon customer with a personalized shopping experience. We achieve our mission through investments in UX, Science, and Systems with the purpose of delivering the future of shopping on Amazon. We are seeking an Applied Scientist to work on step function science improvements across the recommendations space.
About our organization:
Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers. We run global experiments and our work has revolutionized e-commerce with features such as “Customers who bought this item also bought”, “Frequently bought together”, and "Keep shopping for ...". Amazon’s internal surveys regularly recognize us as one of the best engineering organizations to work for in the company, with visible high-impact work, low operational load, respectful work-life balance, and continual opportunity to learn and grow.
About the role:
As an Applied Scientist on the team you will be working on cutting edge ways to help customers find the right products and content on their shopping journey. Our goal is to make step function improvements in the use of advanced Machine Learning (ML) on very large scale datasets. This is an exciting initiative to develop cutting edge ML solutions and apply them to a problem of this magnitude. You will be part of a multidisciplinary team, working on one of the largest scale machine learning systems in the company.
You will hone your skills in areas such as deep learning and reinforcement learning while building scalable industrial systems. As a member of a highly leveraged team of talented engineers and ML scientists, you will have a unique opportunity to help build infrastructure that accesses terabytes of data to produce and deliver models with low latency and high reliability.
You will help define customer focused research initiatives and consult with leadership on the research roadmap.
You will work with partners to address concerns and incorporate subject matter expertise into our modeling efforts.
The goal is to innovate new features and models that can make a huge impact on the customer experience.
You will play a critical role in ideation for the team. We are building the next generation ML system that powers the biggest internet retailer on earth, and we hope you will join us!
Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.
· PhD degree with 4 years of applied research experience or a Masters degree and 6+ years of experience of applied research experience
· 3+ years of experience in building machine learning models for business application
· Experience programming in Java, C++, Python or related language
· Computer Science fundamentals in object-oriented design, data structures, algorithm design, problem solving, and complexity analysis
· Experience building complex software systems that have been successfully delivered to customers
· Ph.D. in Computer Science, Mathematics, Statistics, related field, or equivalent experience.
· 5+ years of hands-on experience in building machine learning models for business applications
· Experience with distributed machine learning systems
· Ability to take a project from scoping requirements through actual launch of the project
· Excellent written and verbal communication skills with the ability to present complex technical information in a clear and concise manner to a variety of audiences.
· A strong sense of curiosity and willingness to learn quickly, building knowledge and skills that this role requires.
· Ability to handle multiple competing priorities in a fast-paced environment.