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Senior Applied Scientist, Amazon Search

Job ID: 2555151 | Services LLC


We are seeking a talented applied researcher to join the Whole Page Planning and Optimization (WPPO) Science team in Search. The latest data from Business Insider shows that almost 50% of online shoppers visit Amazon first. The Search WPPO Science team is responsible for developing reinforcement learning systems for the next generation Amazon shopping experience and delivering it to millions of customers. We believe that shopping on Amazon should be simple, delightful, and full of WOW moments for EVERYONE, whether you are technically savvy or new to online shopping.
As an Applied Scientist, you will be working closely with a team of applied scientists and engineers to build systems that shape the future of Amazon's shopping experience by automatically generating relevant content and building a whole page experience that is coherent, dynamic, and interesting. You will improve ranking and optimization in our algorithm. You will participate in driving features from idea to deployment, and your work will directly impact millions of customers.
You are going to love this job because you will:

* Apply state-of-the-art Machine Learning (ML) algorithms, including Deep Learning and Reinforcement Learning, to improve hundreds of millions of customers’ shopping experience.
* Have measurable business impact using A/B testing.
* Work in a dynamic team that provides continuous opportunities for learning and growth.
* Work with leaders in the field of machine learning.

Joining this team, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging the resources of (AMZN), one of the world's leading internet companies. We provide a highly customer-centric, team-oriented environment.
A successful candidate will have a solid research background in machine learning and reinforcement learning algorithms, customer obsession, great communication skills, and the motivation to achieve results in a fast-paced environment.

We are open to hiring candidates to work out of one of the following locations:

Seattle, WA, USA


- PhD degree with 4+ years of applied research experience or a Master's degree and 6+ years of experience of applied research experience
- At least 5 year of experience with predictive modeling and analysis, applying various machine learning techniques including supervised/unsupervised learning, deep learning, and reinforcement learning
- Publication record at ML conferences and journals
- 5+ years of experience with programming in Java, C++, Python or related language


- At least 8 years of experience with predictive modeling and analysis, applying various machine learning techniques including supervised/unsupervised learning, deep learning, and reinforcement learning
- At least 3 year of experience building large scale production software system * Strong publication record at top ML conferences and journals
- Strong verbal and written communications skills; experience presenting complex technical information, succinctly, to technical and non-technical audiences

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit This position will remain posted until filled. Applicants should apply via our internal or external career site.