Sr Software Development Engineer - Data, AI & Data Platforms (AiDP)

Apple • Austin, TX

1d

About The Position

Athena Platform Services (APS) is looking for a Software Engineer to help build
the data and machine learning platforms that power intelligent risk decisioning
across Apple. Athena enables teams to turn data into action, scaling models and
analytics that detect fraud, prevent abuse, and help protect millions of users
across Apple’s products and services every day.

In this role, you will work with large-scale data to design, build, and enhance
our scalable offline decisioning platform, providing frameworks and tools for
feature engineering, model training, graph databases, and offline analytics.
While familiarity with machine learning concepts is helpful, the primary focus
is on platform engineering, with opportunities to learn ML tools on the job. The
platform ingests hundreds of thousands of TPS transactional data in near real
time, enabling teams to work with large-scale datasets efficiently.

Requirements

• 6+ years building production-grade software or data platforms at scale
• Proficient in Java, Python or Scala for data pipelines, frameworks, or ML workflows Hands-on experience with Spark, Flink, or similar data processing frameworks
• Experience with modern data warehouses (e.g., Snowflake, Iceberg) and streaming platforms (e.g., Kafka)
• Strong skills in designing, optimizing, and debugging large-scale offline data pipelines
• Bachelors of Science in Computer Science or similar degree or equivalent industry experience

Nice To Haves

• Excellent communication skills and ability to analyze and resolve production issues independently
• Demonstrated bias for action, curiosity, and ability to adopt new technologies quickly
• Experience mentoring engineers and fostering technical collaboration
• Strong systems thinking mindset for long-term reliability, scalability, and maintainability
• Passionate about driving innovation through next-generation platforms that optimize offline decisioning and ML workflows for performance, accuracy, and scale
• Exposure to ML/AI ecosystems, including feature engineering, model training pipelines, and GenAI tools
• Familiarity with Kubernetes and cloud-native platform technologies

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees