Description

As an engineer on this growing ML team, you will take on a key role in helping us improve the customer experience of Amazon’s product search engine. We help customers find the products they need, by developing ML approaches that improve several components in the search experience. We are seeking a software engineer who will assist us in deploying those models, integrating them into existing services, and optimizing their performance.

This is a rewarding role where you will be able to draw a clear connection between your work and how it improves the experience of millions of Amazon customers across the globe every day. The team builds ML models trained on terabytes of product and traffic data, and you will play a critical role in building scalable, robust, and maintainable pipelines needed to train, evaluate, and deploy those models. The team is a mixed science/engineering group, with each team member able to contribute to both engineering excellence as well as scientific innovation.

Key job responsibilities

• Design and implement new features across the various software components powering our search system

• Participate in the design and deployment of robust and scalable pipelines for data processing, model training, and model inference

• Build and configure metrics, dashboards, and alerting mechanisms for our deployed services and models

Your will:

• Work on a high-impact, high-visibility product, with your contribution improving the experience of millions of customers

• Design and build pipelines that enable state-of-the-art ML methods to solve real-world problems

• Be a part of a growing team where you can influence the team's mission, direction, and how we achieve our goals

• Publish (if desired) at internal and external scientific venues in the fields of ML/NLP/IR

About the team

The Amazon Search organization owns the software that powers product search — a critical customer-facing feature of Amazon.com. Whenever you visit an Amazon site, anywhere in the world, our technology is what delivers you comprehensive search results at lightning speed.

Within this large organization, our Berlin-based ML team designs, builds, and deploys universal ML models to improve the customer experience and the quality of returned search results. This ensures our customers are more likely to find the products they are searching for. The team is a mixed science/engineering group, which prioritizes work that has high potential for innovation, customer impact, and collaboration.

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

Berlin, BE, DEU

Basic Qualifications

• Bachelor's degree in computer science or a related quantitative field

• 3+ years of professional software development experience

• 1+ year of experience in building large-scale pipelines for data processing and ML model training/inference

• Strong coding and problem-solving skills in at least one modern programming language such as Python, Java, C++, etc.

• A general understanding of essential machine learning concepts (with no expectation of in-depth ML knowledge or research experience)

Preferred Qualifications

• Master's degree in computer science or a related quantitative field

• Professional experience with the AWS family of services (e.g. S3, DynamoDB, EMR, EC2)

• Prior experience designing and implementing large-scale data pipelines and/or ML pipelines

• Prior working experience within a multidisciplinary team of scientists and engineers

• An understanding of, and interest in, search/retrieval engines

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

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