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AI Software Engineer
Full Time
Interested in Machine Learning, and empowering the world to do more and better machine Learning? With Amazon SageMaker, Amazon Web Service's (AWS) Machine Learning platform team is building customer-facing services to catalyze data scientists and software engineers in their machine learning endeavors. This product is a blend of HTTP API's, low and high-level SDK's, and an AWS Console UI.
You will design, implement, test, document, and support cross-cutting services to help customers do machine learning at scale. You'll assist in gathering and analyzing business and functional requirements, and translate requirements into technical specifications for robust, scalable, supportable solutions that work well within the overall system architecture. You will serve as a key technical resource in the full development cycle, from conception to delivery and maintenance. You will produce comprehensive, usable software documentation; recommend changes in development, maintenance and system standards. You will own delivery of entire piece of the system and serve as technical lead on complex projects using best practice engineering standards, and hire/mentor junior development engineers.
Candidate should be a talented engineer that can show initiative, adaptability to challenging environment, problem solving skills, and understanding of Data Engineering. 3+ years industry experience is a must!
Responsibilities
· Create capabilities and abstractions that can enable anyone (engineer or data scientist) to create a scalable ETL pipeline for whatever the purpose is: metrics, analysis, machine learning, dashboard visualizations
· Make intuitive decisions about what services, frameworks, and capabilities need to be in place before they are desperately needed.
· Build and maintain a data collection system that robustly extracts relevant data from multiple sources and data stores
· Proficiency in, at least, one modern programming language such as Scala, Java, Python, Perl
Qualifications
· BA/BS in Computer Science, Information Systems or related technical field.
· 3+ years of experience in Data Engineering, with Cloud SW experience a plus.
· Strong analytical and problem-solving skills.
· Experience in designing and scaling data engineering, models, and pipelines
· Hands-on experience with a variety of data infrastructures, such as:
· Processing: Spark, Flink, Hadoop, Lambda
· Messaging: Kafka, Kinesis
· Storage: Hive, RDS, Athena, DynamoDB
· Machine Learning: Sagemaker, H2O, Keras,
· Open and active in sharing knowledge as well as excellent communication skills
· Programming experience in one or more application or systems languages:
· Scala, Java, Python
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