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Job Details
Posted date: Aug 05, 2024
There have been 2 jobs posted with the title of Machine Learning Data Engineer all time at Amazon.Location: Bellevue, WA
Estimated salary: $162,250
Range: $118,900 - $205,600
Description
The Inventory Planning and Control (IPC) owns Amazon’s global inventory planning systems. We build the systems that decide what, when, where, and how much we should buy to meet Amazon’s business goals and to make our customers happy. We do this for millions of items, for hundreds of product lines worth billions of dollars of inventory world-wide. IPC fosters new game-changing ideas, continuously improves, resulting in sophisticated, intelligent and self-learning models. IPC is unique in that we’re simultaneously developing the science of supply chain planning and solving some of the toughest computational challenges at Amazon. We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.As a Data Engineer with IPC team, you will partner with Software Engineers, Applied Scientists and Data Scientist. You will turn the data requirements of machine learning (ML) and reinforcement learning (RL) models into products that can be used for training and production. In close collaborations with Software Engineers and Senior DEs across teams, you will provide technical expertise and build end-to-end data solutions that are highly available, scalable, stable, secure, and cost-effective. You are passionate about working with huge unstructured, semi-structured and structured datasets and have experience with the organization and curation of data for analytics and model training. You have a strategic and long-term view on architecting advanced data eco systems. You will work on analyzing, cleaning and transform data from various data sets into useable data for ML/RL models. You are experienced in building efficient and scalable data services and have the ability to integrate data systems with AWS tools and services to support a variety of customer use cases/applications.
Key job responsibilities
• Designing, implementing, and maintaining data infrastructure to support a wide variety of large and complex data sets, ensuring high performance, availability, and integrity for RL/ML models.
• Ability to analyze data from various sources, develop and execute Python notebooks for validating the data consumptions needs of the models.
• Implement data ingestion routines both real time and batch using best practices in data modeling, ETL/ELT processes by leveraging AWS technologies and big data tools.
• Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.
• Collaborate with engineers to help adopt best practices in data system creation, data integrity, test design, analysis, validation, and documentation.
• Collaborate with applied and data scientists to create fast and efficient algorithms that exploit our rich data sets for optimization, statistical analysis, prediction, clustering, and machine learning.
• Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service modeling and production support for customers.
• Develop comprehensive monitoring, alarming, and data quality controls for all of the above.
A day in the life
The IPC science team is building a wide range of ML applications to solve challenging problems in optimizing Amazon's supply chain performance. You will work with colleagues from different technical backgrounds to develop and implement ML solutions in production.
About the team
We focus on innovation, and promote experimentation and learn by building. We often tackle the hardest and most ambiguous problem in the organization and work cross-functionally. We are at the center of developing inventory solutions to support the rapid growth of Amazon's store business.
Qualifications
- 3+ years of data engineering experience- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Knowledge of distributed systems as it pertains to data storage and computing
- Experience with data modeling, warehousing and building ETL pipelines
- Experience working on and delivering end to end projects independently
- Experience programming with at least one modern language such as C++, C#, Java, Python, Golang, PowerShell, Ruby
- Experience with Redshift, Oracle, NoSQL etc.
Extended Qualifications
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
- Familiarity with various AI/ML modeling techniques and the ability to adapt to different project requirements.
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 $118,900/year in our lowest geographic market up to $205,600/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.
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