Backed by General Catalyst, Khosla and Sequoia.
About the role
Data Ingestion & Processing: Design and build high-throughput pipelines that validate, transform, and featurize raw multimodal data. Batch & Streaming Systems: Operate large-scale batch and streaming workflows over massive datasets.
What they're looking for
- Experience with large ML training pipelines or dataloading systems
- Knowledge of columnar or custom data formats
- Experience with systems like ClickHouse, Ray, Flink, Spark, or similar
- Hands-on experience operating petabyte-scale datasets
- Debugging and fixing performance bottlenecks in data-heavy systems
- Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records
More about this role
Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.
As an ML Infra Engineer (Data Systems), you’ll build and operate the data infrastructure that powers large-scale robot learning. Your systems will sit directly between raw data sources and training/evaluation, enabling us to move faster while maintaining performance, correctness, and reliability at scale.
This is a systems role at the intersection of distributed systems, storage, and machine learning infrastructure.
The Infrastructure organization builds the foundations that make large-scale learning possible at PI. This includes training systems, data platforms, evaluation pipelines, and the tooling that allows researchers and roboticists to work with massive datasets safely and efficiently.
Data Ingestion & Processing: Design and build high-throughput pipelines that validate, transform, and featurize raw multimodal data.
Batch & Streaming Systems: Operate large-scale batch and streaming workflows...
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