Machine learning big data; realtime data streaming. If these areas resonate with you then join us to work on extremely motivating challenges at Amazon Web Services (AWS). Within AWS Payments we build and run Machine Learning models to optimize business processes and improve the customer experience.
If you are a strong software engineer selfstarter and learner who is passionate about working with massive amounts of data to build stateofart system on top of AWS native services then this is the right opportunity for you. You will work with a team of highly skilled engineers and scientists to build the next generation Machine Learning Data and Analytics platform at AWS. As part of your job you will deal with large amounts of training data rapid prototyping of new models performance optimizations offline and online testing and building fully automated solutions to push Machine Learning models to production applying MLOps bestpractices.
About you
You are fascinated by the power of large scale systems and using machine learning algorithms to optimize decision making. And youre looking for a career where youll be able to build to deliver and to impress. You look at problems holistically and thrive on the intricate complexity of designing feedback loops and ecosystems. You want to work on projects where you are implementing solutions to real problems that require creative solutions and deep understanding of the problem space. You will partner with research scientists to challenge yourself and others to constantly come up with better solutions. Youll be given an opportunity to own and drive initiatives through the entire software stack from customer facing features to algorithmic innovation all the way down to the datasets that the backend services consume.
As a software development engineer of this team you will play a pivotal role in shaping the definition vision design roadmap and development of this set of product features from beginning to end. You will:
Mentor and lead junior developers on the team.
Help drive business decisions with your technical input.
Design implement test deploy and maintain innovative software solutions while optimizing service performance durability cost and security.
Use software engineering best practices to ensure a high standard of quality for all of the team deliverables.
Participate in the full development cycle for ETL: design implementation validation documentation and maintenance.
Design implement and support data warehouse / data lake infrastructure using AWS big data stack Python Redshift Glue/lake formation EMR/Spark/Scala Athena etc.
Write high quality distributed and scalable systems to deal with large scale data.
Automate the endtoend development lifecycle to deploy Machine Learning models from research phase to production.
Work in an agile startuplike development environment where you are always working on the most important stuff.
Work closely with scientists data engineers and other stakeholders to create and deploy new features in order to optimize various business processes.
In this role you will contribute to a critical and highlyvisible function within the AWS business. You will be given the opportunity to autonomously deliver the technical direction of new projects and features in our roadmap. You will work with extraordinary talent and have the opportunity to hire and shape the team to best execute on the product. If youre excited to have a large impact on AWS and the cloud computing industry youll find this role to be engaging challenging and full of opportunities to learn and grow.
About our team
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures and were building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy oneonone mentoring and thorough but kind code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a betterrounded engineer and enable them to take on more complex tasks in the future.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures and were building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy oneonone mentoring and thorough but kind code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a betterrounded engineer and enable them to take on more complex tasks in the future.
Learn more about Amazon on our Day 1 Blog: all of this sounds exciting to you then please come join us and help shape the future.
3 years of noninternship professional software development experience
2 years of noninternship 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
Bachelors degree in computer science or equivalent
Experience building and optimizing big data pipelines architectures and data sets
Experience using big data technologies (Hive Hbase Spark EMR etc.
Advanced working SQL knowledge and Experience working with relational databases
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 disability age or other legally protected status.
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The base salary for this position ranges from $114800/year up to $191800/year. Salary is based on a number of factors and may vary depending on jobrelated knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity signon 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. Applicants should apply via our internal or external career site.