Staff / Sr. ML Engineer, Indexing Infrastructure - Jobs - Careers at Apple
- Design and build our web signal store, a petabyte-scale Parquet/Iceberg lakehouse holding trillions of web documents and signals.
- Design and build our in-house MapReduce-style processing framework, which runs thousands of workers on Kubernetes.
- Improve performance, reliability, and cost at trillion-row scale, from read/write throughput and compaction to fault-tolerant batch jobs on shared clusters.
- Own production health, including monitoring, on-call, and root-cause fixes, and raise the engineering bar through design and code reviews.
- Strong coding skills and a solid computer science background in algorithms, data structures, and distributed systems
- 5+ years experience designing, building, and operating large-scale distributed systems such as databases, storage platforms, or data processing frameworks
- Hands-on experience with petabyte-scale batch data processing (MapReduce, Spark, or similar)
- Proficiency in cloud-native architectures and compute orchestration on AWS (S3, EC2, EKS) and Kubernetes
- Excellent interpersonal skills, with the ability to work independently and drive cross-team efforts
- MS or PhD in Computer Science or related field
- Deep familiarity with columnar and lakehouse formats (Parquet, Iceberg), and the judgment to choose between them at scale
- Experience with storage internals: compaction, metadata and manifest management, indexing, and query performance tuning
- Experience with workflow orchestration (e.g., Argo) and resource scheduling on shared Kubernetes clusters
- Experience with key-value or online serving stores (e.g., Bigtable, HBase, Cassandra) and multi-cloud data movement
- Experience with search indexing, machine learning, or NLP is a plus
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🇬🇧 English