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Machine Learning Engineer - Strategic Data Solutions

Apple· Machine Learning and AI
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Hybrid (Austin)Not specifiedPosted 1w ago

About the role

SDS Machine Learning Engineer role focused on building end-to-end predictive solutions to improve security, fraud prevention, and operational efficiency across Apple. Involves engaging with business teams, designing data science approaches, collaborating with data engineers, and deploying real-time and batch decisioning while monitoring production metrics and adapting to adversarial trends.

Responsibilities

  • Engage with business teams to identify opportunities, understand requirements, and translate them into technical solutions.
  • Design data science approaches and develop algorithms to address business problems.
  • Collaborate with data engineers and platform architects to implement robust production real-time and batch decisioning solutions.
  • Ensure operational and business metric health by monitoring production decision points.
  • Investigate adversarial trends, identify behavior patterns, and respond with agile logic changes.
  • Communicate results of analyses to business partners and executives.

Qualifications

  • Education in a quantitative field (Computer Science, Applied Mathematics, Statistics) or equivalent professional experience.
  • Practical experience with and theoretical understanding of algorithms for classification, regression, clustering, and anomaly detection.
  • Working knowledge of relational databases (SQL) and large-scale distributed systems (Hadoop, Spark).
  • Ability to implement data science pipelines and applications in Python, Scala, or Java.
  • Ability to comprehend and debug complex systems integrations across toolchains and teams.
  • Ability to extract meaningful business insights and tell the stories behind patterns.
  • Excellent presentation skills for concise business-focused communication.
  • Creativity to engineer novel features/signals and push beyond current tools.
  • Experience with images, training/deploying CNN models in production, and Computer Vision techniques.

Skills

Required:Data science problem framing and requirements gatheringPredictive modeling and statistical analysesMachine learning algorithms (classification, regression, clustering, anomaly detection)Production data pipelinesSQL and relational databasesDistributed systems (Hadoop, Spark)Programming in Python/Scala/JavaCommunication and storytelling with dataSystem integration debugging
Nice to have:Computer Vision / CNNs

Benefits

  • Not specified in the description.
Last updated Oct 16, 2026. Interested? Apply on the company site.

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