Rerun – Dataframe SDK Engineer
About the role
Own and expand the query and dataframe SDK that makes exploring Physical AI data in Rerun intuitive and powerful. You'll work across Python, Rust, and gRPC layers — improving performance, ergonomics, and integrations for robotics and embodied AI data pipelines. The role sits at the intersection of API design, query performance, and developer experience. Note: Rerun has a stated preference for European or US-East Coast timezone overlap (1:30–5:00pm CET); candidates outside these regions are considered case-by-case — verify timezone compatibility before applying.
What you'll do
- Build a world-class query and dataframe SDK that makes exploring multimodal AI data in Rerun intuitive and powerful
- Work across Python, Rust, and gRPC layers to add new operations and integrate with distributed backend services
- Push performance improvements through better query planning, push-down logic, and dataset versioning
- Contribute documentation and examples that accelerate SDK adoption for Physical AI teams
- Collaborate with engineers on dataset creation, versioning, and catalog interfaces for Rerun Cloud
Requirements
- Experience building or contributing to Python data APIs, ideally dataframe-style (Pandas, Polars, Arrow, Snowflake, or similar)
- Strong Python and Rust, or language-agnostic background with proven ability to pick up Rust rapidly
- Experience writing high-performance software and debugging across Python, Rust, gRPC, and distributed systems
- Proven ability to own projects end-to-end with limited supervision; comfortable owning a slice of the stack
- Empathy for developers and taste for clean, ergonomic API design
- Preferred: Apache Datafusion/Arrow experience, query planner familiarity, multimodal data systems background (robotics, simulation)
About Rerun
Rerun builds the Multimodal Data Stack for Physical AI — open-source tools for logging, visualizing, and querying multimodal data from robotics, autonomous systems, and simulation pipelines. Their commercial platform handles ingesting, storing, and building training data pipelines for Physical AI at scale.
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