Job description

With the expansive data we have, our job is to build meaningful data relationships and engagement experiences for our internal customers. If you’re interested in being a part of a team that’s constantly learning and problem-solving, we’d love to talk with you. As a Software Engineer on the SDS team, you will work closely with Machine Learning Engineers and other Software Engineers to lead the design and implementation of systems and tools to support the ML initiatives for Apple Retail and Fraud prevention efforts of SDS. You will be: • Developing and implementing production software for retail ML initiatives and preventing retail fraud • Responsible for system architecture design • Working with external infrastructure teams to drive the development of infrastructure needs • Innovating by recognizing opportunities for automation and tools improvements • Responsible for developing and implementing process improvements to bring efficiency and stability to fraud analytics • Responsible for technical leadership for a team of data scientists • Responsible for Release engineering and ML Operations • Expected to operate independent of supervision, with limited guidance • Lead the team to increase the level of maturity and skill in analytical software development BS or advanced degree in Computer Science, related field or equivalent experience Mastery of one of Java, Python, or equivalent language Experience with Big Data & building ETL Data Pipelines Experience with messaging systems, such as Kafka 8+ years of experience in software engineering/data science Experience building data science or data analysis tools on AWS/GCP/Cloud based systems Experience with Docker, Kubernetes, or cloud platform deployment Experience with Relational databases and NoSQL databases Demonstrated understanding of the full software development lifecycle Excellent problem solving, critical thinking, and communication skills Solid grasp of computer science fundamentals including data structures and algorithms Solid ability to evaluate and apply new technologies in a short time Self-motivated, proactive, and solution-oriented

Requirements

Must-haves

Developing and implementing production software for retail ML initiatives and preventing retail fraud
Responsible for system architecture design
Working with external infrastructure teams to drive the development of infrastructure needs
Innovating by recognizing opportunities for automation and tools improvements
Responsible for developing and implementing process improvements to bring efficiency and stability to fraud analytics
Responsible for technical leadership for a team of data scientists
Responsible for Release engineering and ML Operations
Expected to operate independent of supervision, with limited guidance
Lead the team to increase the level of maturity and skill in analytical software development
BS or advanced degree in Computer Science, related field or equivalent experience
Mastery of one of Java, Python, or equivalent language
Experience with Big Data & building ETL Data Pipelines
Experience with messaging systems, such as Kafka
8+ years of experience in software engineering/data science
Experience building data science or data analysis tools on AWS/GCP/Cloud based systems
Experience with Docker, Kubernetes, or cloud platform deployment
Experience with Relational databases and NoSQL databases
Demonstrated understanding of the full software development lifecycle
Excellent problem solving, critical thinking, and communication skills
Solid grasp of computer science fundamentals including data structures and algorithms
Solid ability to evaluate and apply new technologies in a short time
Self-motivated, proactive, and solution-oriented

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningmljavapythonawsgcpdockerkubernetes

Platform: apple
Effort: medium

Benefits

Benefits detected in the listing.

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