Applied Scientist I (Level 4) - Search, AEE Relevance

Key Skills

C++, JavaScript, Oracle, RDBMS, SQL

Job Description

Amazon Expansion and Exports (AEE) Search team creates, customer-focused Search ranking and relevance solutions. Our ranking models and services powers the experience when customer visits Amazon site worldwide and types in a query or browses through product categories. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day.

AEE Relevance team has a mission to solve customer problems that require advancing the state of the art in machine learning. We work backwards from the customer to create value for them by addressing an underlying, unsolved scientific problem. We deploy our solutions through distributed systems that operate at millisecond latencies at Amazon scale. We strive to publish our solutions and open-source our software so that the broader scientific community can benefit.

As an applied scientist on our team, your role is to leverage your strong background in Computer Science, Reinforcement Learning, and Machine Learning to help build the next generation of our model development and assessment pipeline, harness and explain rich data at Amazon scale, and provide automated insights to improve machine learned solution that impact millions of customers every day. This role requires a pragmatic technical leader comfortable with ambiguity, capable of summarizing complex data and models through clear visual and written explanations. The ideal candidate will have experience with machine learning models and information retrieval system. We are particularly interested in experience applying deep learning, and reinforcement learning at scale. Additionally, we are seeking candidates with strong rigor in applied sciences and engineering, creativity, curiosity, and great judgment.

Your responsibilities include:

• Analyze the data and metrics resulting from traffic into Amazon's product search services.
• Design, build, and deploy effective and innovative ML solutions to improve various components of the search stack, such as indexing, ranking, and query autocompletion.
• Evaluate the proposed solutions via offline benchmark tests as well as online A/B tests in production.
• Publish and present your work at internal and external scientific venues in the fields of ML/RL/NLP/IR.

Your benefits include:

• Working on a high-impact, high-visibility product, with your work improving the experience of millions of customers around the world.
• The opportunity to use (and innovate) state-of-the-art ML and RL methods to solve real-world problems.
• Excellent opportunities, and ample support, for career growth, development, and mentorship.

AEE Relevance team operates primarily out of Amazon's Austin office. We are a new and expanding team where you will have an opportunity to influence our goals and mission. We are a mix of applied scientists and software engineers who collaborate with other teams within Amazon Search to solve and deploy machine learning solutions at scale.

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

Austin, TX, USA

BASIC QUALIFICATIONS

• Experience programming in Java, C++, Python or related language
• Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse

PREFERRED QUALIFICATIONS

• Experience implementing algorithms using both toolkits and self-developed code
• Have publications at top-tier peer-reviewed conferences or journals