Machine Learning Engineer II, International Seller Growth

Seattle, Washington, USA

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Job summary
Come and be part of the International Seller Services Central analytics team and work on solving cutting edge ML problems!

We are a team of BIEs, DEs, ML Engineers and Scientists who support the seller services org to provide data driven analytical solutions to help sellers grow on Amazon worldwide. We support Applied Scientists, Data Scientist, and Economists who experiment, research, and turn machine/deep learning and AI research into great products for our customers.

We are seeking a smart, highly-motivated, and experienced Data Engineer/Developer to work on building scalable solutions to productionalize and train ML models and work with partner teams to push these models onto Amazon seller central portal.

Key job responsibilities
Key Responsibilities:
Design and deliver big data architectures for experimental and production system
· Develop machine learning workflows and integrate with AI Workbench and other AWS solutions
· Develop and maintain datasets in AWS Dynamo DB & AWS S3
· Leverage EMR to preprocess, cleanse and transform large volume of data sets
· Orchestrate step functions using python
· Optimize large scale data extraction pipelines to enhance user experience
· Collaborate with Data Scientists, Product managers, Software engineers and ISS Senior leadership and work towards achieving organizations goals
· Innovate and drive strategic decisions during design discussions with stakeholders of the project(Data scientists, SDE’s, Project managers & Senior ISS Leadership)
· Develop and support mission critical application which is widely used by sellers across the globe

Basic Qualifications

· 3+ Years of experience as a ML Engineer / Data engineer in to ML domain with proven expertise in at least one database technology such as Hadoop, EMR, Redshift, Spark or Scala and one ML model implementation
· Coding proficiency in Python, Shell & Spark
· Experience with scalable model training leveraging big data platform
· Experience with ML libraries/frameworks such as Tensorflow, AWS Sagemaker, Keras etc.
· Experience developing and supporting machine learning production system
· Experience with at least one massively parallel processing data technology such as Spark or Hadoop based big data solution
· Experience in building highly available distributed systems of data extraction, ingestion and processing of large data sets
· Excellent stakeholder management and proven communication skills with both business and technical teams
· A desire to work in a collaborative, intellectually curious environment with a strong “Learn and Be Curious” attitude
· You should have excellent business and communication skills to be able to work with business owners to develop and define key business question

Preferred Qualifications

xperience working with AWS cloud environment with a strong understanding of DDB, S3, Redshift, Step functions etc.
· Experience working with both supervised and unsupervised machine learning models
· Experience working with Orchestration tools such as Apache Airflow
· Experience working with Amazon Sage maker (AWS Machine Learning Platform)
· Experience in operating multilevel abstraction when training and deploying machine learning models
· Knowledge of Advanced Statistics and implementing ML models.

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

Tags: Airflow AWS Big Data Deep Learning Distributed Systems Hadoop Keras Machine Learning ML ML models Model training Python Redshift Research SageMaker Scala Spark Statistics TensorFlow

Region: North America
Country: United States
Job stats:  14  1  0

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