Strong systems thinking, communication, and problem-solving skills.
Demonstrated bias for action, curiosity, and ability to learn new technologies quickly.
Experience with ML/AI platforms, including feature engineering, model training, or GenAI workflows.
Familiarity with Kubernetes and cloud-native technologies.
Experience with Alibaba Cloud or other cloud platforms in regulated or region-specific environments, including PIPL.
Experience mentoring engineers and driving technical collaboration.
Experience with Scala
3+ years building production-grade software or data platforms at scale.
Proficient in Python or Java
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
AI & Data Platforms (AiDP) is IS&T's engine for AI-powered innovation. The team brings together data, application development, and machine learning - including generative AI - along with data services and customer success functions, to help IS&T build solutions more efficiently and streamline the adoption and embedding of generative AI across Apple.
Athena Platform Services (APS) is looking for a talented Software Engineer to play a meaningful role in building data services and platforms that run machine learning analytics to prevent fraud, waste and abuse across Apple. Athena is a machine learning platform committed to providing high-quality, data-driven risk decisioning. We are passionate about operational excellence and providing data-driven solutions with meaningful results!
Description
As a Software Engineer on the Athena platform, you will be working with large-scale data and decisioning platforms used by data scientists, analysts, and business partners. This position supports both online solutions for near-real-time decisioning, and offline solutions for batch analytics and reporting.
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
Other benefits are as per company policy.
Work at office
Full time
Austin, TX
Applications for this job are handled on the company's own website.
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