CloudKitchens

Build log ingestion, indexing, retrieval, replay, and open-loop and closed-loop scoring pipelines.Develop deterministic scenario execution with clock control, seed management, configuration management, and software-version traceability.Integrate simulation workloads into commit, nightly, regression, and continuous integration workflows.Define release pass criteria and metrics and bu

Own the simulation platform architecture, including simulation control, run identity, determinism, reproducibility, batch execution, and log storage and indexing.Build and manage log-replay pipelines, including replayable test cases, open-loop scoring against ground truth, and closed-loop replay.Own scenario schemas, scenario libraries, coverage definitions, and commit, nightly, reg

Design, build, and maintain scalable ML infrastructure for storage, pipeline management, environment setup, checkpointing, metadata management, and experiment tracking.Create self-service ML workflows and tooling for ML engineers and data scientists.Build automated ETL and data ingestion pipelines that transform robot telemetry into datasets for training and analytics.Develop Terraf