Staff / Sr. ML Engineer, Indexing Infrastructure
Confirmed on the employer's own hiring board on Oct 31, 2026. First seen by Alion on Oct 29, 2026. Apple scores A on the Alion truth index.
Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.
Do you want to make Siri and Apple products smarter for our users? The MLPT & Infra teams are building groundbreaking technology for algorithmic search, machine learning, natural language processing, and artificial intelligence. Our universal search engine powers search features across a variety of Apple products, including Siri, Spotlight, Safari, Messages and Lookup.
Description
As part of this group, you will build the storage and compute foundation behind one of the most exciting high-performance computing environments: trillions of records, petabytes of data, and the systems that turn them into search and Apple Intelligence experiences that delight our customers every day.
Minimum Qualifications
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
Preferred Qualifications
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