Athena AI & Data Platforms Engineer

Apple Inc.; Austin (TX); On-site; USD 140,000 - 170,000; Full time

Job summary

Apple Inc. in Austin, Texas, is seeking a Software Engineer to join the Athena, Ai & Data Platforms (AiDP) team. You will help build data services and platforms that run ML analytics to prevent fraud, waste and abuse across Apple. This role supports both near-real-time decisioning and batch analytics for reporting.

You will work with large-scale data, establish CI/CD practices, and contribute to cost and performance optimizations while collaborating with data scientists and software engineers.

Qualifications

• 5+ years building production-grade software or data platforms at scale.
• Proficient in Java, Python, or Scala.
• Hands-on experience with Spark, Flink, Kafka, or similar distributed data technologies.
• Experience designing, optimizing, and debugging large-scale production data pipelines.
• Bachelor’s degree in Computer Science or a related technical major

Responsibilities

• Turn business and ML requirements into scalable platform and decisioning systems
• Build resilient, low-latency services for real-time inference and streaming data
• Define gold-standard CI/CD, observability, and SLA practices for Data and ML
• Ship automated pipelines powering features, training, and online serving
• Drive performance and cost optimizations across Data and ML workloads
• Own data and model health with monitoring, validation, and drift detection

Skills

Java

Python

Scala

Distributed data systems

Education

Bachelor's degree in Computer Science or related technical field

Tools

Spark

Flink

Kafka

Job description

Apple Inc. in Austin, Texas, is seeking a Software Engineer to join the Athena, Ai & Data Platforms (AiDP) team. You will help build data services and platforms that run ML analytics to prevent fraud, waste and abuse across Apple. This role supports both near-real-time decisioning and batch analytics for reporting.

You will work with large-scale data, establish CI/CD practices, and contribute to cost and performance optimizations while collaborating with data scientists and software engineers.