Software Development Engineer, ADSP: Bidding Science and Engineering
Amazon.com
Interested in working at the intersection of high-scale engineering, Machine Learning and Applied Science?
At Amazon Advertising, we are developing state-of-the-art large-scale computational advertising and real-time application. The Bidding and Pacing Engineering team develops algorithms and high performance, large-scale distributed systems to optimize ad selection, bidding and campaign performance. Our systems process billions of ad impressions daily from across the internet to power our display advertising algorithms. Our engineers work with machine learning scientists, economists and product managers on high impact initiatives for Amazon’s Display Advertising.
As an engineer on the team you will design and develop products that are at the heart of advertising – products that determine how billions of impressions are allocated to advertisers and how much advertisers pay for those impressions. You will have responsibility to help define requirements, create software designs, implement code to these specifications, define continuous integration testing and support products while deployed and used by our customers. You will have complete ownership of technology choices, architecture, A/B testing for your features, code deployments into production environment and operations for the products you own. Your team will include Applied scientists, product managers and other high performing engineers. We’re looking for SDEs interested in developing real-time bid and optimization algorithms on large scale systems that process tens of billions of requests/ day.
Key job responsibilities
You will have responsibility to help define requirements, create software designs, implement code to these specifications, define continuous integration testing and support products while deployed and used by our customers.
A day in the life
You will work closely with Applied Scientists, Data Scientists, Product Managers and high performing Software Engineers to simulate campaign optimization strategies and implement the strategies in large scale systems.
At Amazon Advertising, we are developing state-of-the-art large-scale computational advertising and real-time application. The Bidding and Pacing Engineering team develops algorithms and high performance, large-scale distributed systems to optimize ad selection, bidding and campaign performance. Our systems process billions of ad impressions daily from across the internet to power our display advertising algorithms. Our engineers work with machine learning scientists, economists and product managers on high impact initiatives for Amazon’s Display Advertising.
As an engineer on the team you will design and develop products that are at the heart of advertising – products that determine how billions of impressions are allocated to advertisers and how much advertisers pay for those impressions. You will have responsibility to help define requirements, create software designs, implement code to these specifications, define continuous integration testing and support products while deployed and used by our customers. You will have complete ownership of technology choices, architecture, A/B testing for your features, code deployments into production environment and operations for the products you own. Your team will include Applied scientists, product managers and other high performing engineers. We’re looking for SDEs interested in developing real-time bid and optimization algorithms on large scale systems that process tens of billions of requests/ day.
Key job responsibilities
You will have responsibility to help define requirements, create software designs, implement code to these specifications, define continuous integration testing and support products while deployed and used by our customers.
A day in the life
You will work closely with Applied Scientists, Data Scientists, Product Managers and high performing Software Engineers to simulate campaign optimization strategies and implement the strategies in large scale systems.
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