Machine Learning Engineer – Recommendations & Personalization (Feature Engineering)

Apple • Seattle, WA

3h

About The Position

In this role, you will be responsible for operationalizing machine learning models—from building real-time and batch inference pipelines to optimizing system performance, reliability, and experimentation velocity. You’ll help bridge the gap between research and production by developing the infrastructure, tooling, and monitoring required to ship ML-driven features safely and efficiently. If you are an engineer who enjoys scaling ML solutions, building production-grade services, and driving experimentation across billions of users, this is your opportunity to make a meaningful impact.

Requirements

• MS or PhD in Computer Science, Software Engineering, or related field.
• 2+ years of experience in production machine learning systems, especially for personalization or recommendations.
• Experience with big data and stream processing frameworks like Spark, Flink, or Kafka.
• Proficiency in object-oriented programming languages such as Java, Scala, or C++.
• Experience building and maintaining large-scale distributed systems for ML workloads.
• Deep understanding of ML model deployment pipelines, runtime optimization, and system integration.
• Familiarity with A/B testing frameworks, experimental design, and online evaluation.
• Strong focus on system reliability, latency, and observability in production environments.

Nice To Haves

• Experience in batch and real-time inference serving, including autoscaling and traffic management.
• Background in content recommendation systems, search ranking, or user engagement optimization.
• Experience with CI/CD workflows for ML systems, including safe model rollouts and shadow testing.
• Exposure to containerized deployments and orchestration (Kubernetes, Docker).
• Experience building and deploying production-grade applications using LLMs, including expertise in prompt engineering, RAG pipelines, and framework orchestration.
• Proven track record of developing autonomous agents capable of multi-step reasoning, external tool integration, and complex task decomposition to solve open-ended problems.
• Prior experience working on consumer-scale media products (apps, games, books, music, or video).

What This Job Offers

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