1 month ago
Cupertino, CA, USAEntry Level / Mid Level
H1B sponsor
Responsibilities
- Build secure, scalable data and machine learning systems across real-time, near-real-time, and batch execution contexts.
- Design and deliver pipeline architecture, ML model development, training, deployment, and privacy-preserving infrastructure.
- Drive reliability, performance, efficiency, schema-change, backfill, experimentation, and testing improvements.
- Apply business, analytics, and engineering understanding to create reusable and efficient solutions.
- Use LLMs and AI coding agents for implementation, testing, debugging, code review, and evaluation while validating correctness, privacy, and cost.
- Collaborate with engineers and product managers, participate in code and design reviews, and mentor others as seniority increases.
- Contribute to on-call, monitoring, incident response, root-cause analysis, and continuous reliability improvements.
Requirements
- At least 1 year of industry experience building scalable data pipelines and machine learning systems or other distributed software at scale.
- Strong computer science and software engineering fundamentals, including data structures, algorithms, and system design.
- Proficiency in modern programming languages such as Rust, Python, Java, or Scala.
- Experience with distributed systems and data processing technologies such as Spark, Kafka, or Flink.
- Experience building and scaling systems on premise and in the cloud.
- Hands-on daily engineering experience with LLMs such as Claude or Gemini for code generation, review, debugging, test writing, agentic loops, and evaluation systems.
- Effective communication and collaboration with technical and non-technical cross-functional teams.
- BS or MS in Computer Science, Software Engineering, Distributed Systems, or a related field.
- Experience with NoSQL datastores such as Cassandra, Keyspaces, or ElastiCache is preferred.
- Experience with lakehouse and Iceberg table formats, anomaly detection, and A/B experimentation frameworks is preferred.
- Experience driving reliability, efficiency, or cost improvements and mentoring engineers is preferred.
- Prior advertising-industry experience is a plus.
Tech Stack
Categories
Data EngineeringML Engineering
About Apple
Apple designs and sells consumer electronics, software, and services for consumers and professionals worldwide, including iPhone, Mac, iPad, Apple Watch, and AirPods, plus platforms like iOS/macOS and services such as the App Store, iCloud, Music, and TV+. Its business combines device sales with services and subscriptions and in-house silicon design. Founded in 1976, Apple is headquartered in Cupertino, California, and trades on NASDAQ as AAPL.