Staff ML Engineer - Ads Data Pipelines

Apple Inc.; Austin (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Apple Inc. in Austin, Texas is hiring a hands-on Machine Learning Engineer to design and build ML systems and data pipelines that safeguard advertiser trust and improve invalid traffic protections.

You will define an innovation roadmap, deploy models with CI/CD, feature stores, and streaming infrastructure (Kafka/Spark/Flink), and run A/B experiments. You will lead performance tuning, calibration, and drift detection to deliver measurable improvements in product quality, latency, and cost, while

Qualifications

• 8+ years of experience building machine learning capabilities across many product areas at scale.
• Strong proficiency in Java, Python, or Scala for algorithm and system development.
• Experience with distributed systems and big data frameworks such as Spark, Kafka, Hadoop, or Flink.
• Familiarity with CI/CD workflows, cloud environments, and containerized deployments.
• Understanding of statistical methods, A/B testing, and online experimentation frameworks.

Responsibilities

• Develop and manage end-to-end lifecycle of machine learning models with observability for large-scale systems.
• Design and optimize distributed algorithms and data processing frameworks (e.g., Spark).
• Implement scalable feature pipelines to ingest, clean, transform, and analyze massive datasets.
• Reinforce Ads integrity and advertiser trust through robust infrastructure.
• Collaborate with product and engineering teams on production systems and applications.

Skills

Java

Python

Scala

Education

BS or MS in Computer Science, Software Engineering or related technical fields

Tools

Spark

Kafka

Hadoop

Flink

Job description

Apple Inc. in Austin, Texas is hiring a hands-on Machine Learning Engineer to design and build ML systems and data pipelines that safeguard advertiser trust and improve invalid traffic protections.

You will define an innovation roadmap, deploy models with CI/CD, feature stores, and streaming infrastructure (Kafka/Spark/Flink), and run A/B experiments. You will lead performance tuning, calibration, and drift detection to deliver measurable improvements in product quality, latency, and cost, while