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.

Description

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.","responsibilities":"Build scalable offline decisioning platforms and frameworks to support feature engineering, model training, and offline analytics.

Develop automated pipelines and tools for managing large-scale data and ML workflows.

Drive innovation, building next-generation platforms that act as a force multiplier for ML and data science teams.

Define and enforce best practices for CI/CD, observability, and platform reliability.

Optimize performance, cost, and data quality, including monitoring, validation, and drift detection.

Mentor and guide junior engineers, fostering technical growth and knowledge sharing across the team.

Preferred Qualifications

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

Minimum Qualifications

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

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .