ML Infra Engineer (Data Systems) (AI)

Location: San Francisco, United States; on-site

Company

hirify.global develops foundation models and learning algorithms for robots and physically actuated devices.

What you will do

• Design and build high-throughput pipelines for validating, transforming, and featurizing raw multimodal data.
• Operate large-scale batch and streaming workflows over massive datasets.
• Design object storage layouts, metadata systems, file formats, and efficient data access patterns.
• Build data lifecycle systems for backfills, dataset rebuilds, garbage collection, and large-scale transformations.
• Optimize dataloaders, sharding, prefetching, caching, and throughput to reduce the time from data arrival to model training.
• Implement metadata indexing, petabyte-scale data movement, observability, validation, and guardrails while collaborating with researchers, engineers, and roboticists.

Requirements

• Strong software engineering fundamentals.
• Experience building distributed systems or large-scale data pipelines.
• Ability to reason about performance, memory, I/O, and storage efficiency.
• Familiarity with batch and/or streaming processing systems.
• Experience with object storage systems and data format tradeoffs.
• Ownership of designing, building, operating, and iterating on systems end to end.

Nice to have

• Experience with large machine learning training pipelines or dataloading systems.
• Knowledge of columnar or custom data formats.
• Experience with ClickHouse, Ray, Flink, Spark, or similar systems.
• Hands-on experience operating petabyte-scale datasets.
• Experience debugging and fixing performance bottlenecks in data-heavy systems.

Culture & Benefits

• Work on-site within an infrastructure organization supporting large-scale learning.
• Collaborate closely with researchers, engineers, and roboticists on fast-moving projects.
• Build and operate systems that prioritize performance, correctness, reliability, and operational ownership.