- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
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 https://www.amazon.jobs/en/disability/us.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Are you excited about operating at Internet scale? Do you want to work at the intersection of Machine Learning, Data Science, and Causal Inference? Do you like inventing, growing and learning from the world-class engineers and scientists? If so, we want to hear from you!
Key job responsibilities
You will be responsible for designing and developing software products that will provide measurement data to a wide set of users across all of Amazon's advertising suite. You will be able to demonstrate a variety of approaches and design patterns and have a demonstrated competence in designing maintainable and scalable software written in a high-level language. You'll work with Data & Applied Scientists, Economists, and other senior technical leaders who are advancing measurement science and causal inference. You will show your ability to adapt to changing technical environments and devise creative solutions to vexing software problems. You will encounter some of the toughest and most inspiring technical challenges of your career as you build petabyte-scale services, invent new big data paradigms, and scale for extreme growth.
A day in the life
We measure the effectiveness of ads through a range of causal measurement and modeling techniques, including scientific experiments and ML. We do this to enable advertisers to optimize ad spend and allocate budgets effectively by providing accurate, actionable and timely causal measurement for all Amazon ad products. We use a combination of deterministic and modeled measurement techniques to produce the estimates that are fast, accurate, and actionable. We apply the latest AWS big data and machine learning technologies on over 50 billion new events per day, operating petabyte size clusters. We constantly invent on our cutting-edge event-driven architectures to stay ahead of growing scale.
About the team
This team is building the core causal measurement and modeling capabilities serving all Amazon Ads. We work with a variety of systems and languages: combining AWS services like EMR, Kinesis and AWS Batch, with open source technologies such as Spark, Presto and PyTorch.
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