You will work across robot middleware (ROS 2), distributed systems, cloud infrastructure, and ML data pipelines to create reliable, high-performance components that power robotic learning, deployment, and real-time operation. • Drive ML data pipelines - Develop ingestion, preprocessing, and storage pipelines for multimodal datasets; support large-scale training workflows. • Cloud & distributed infrastructure - Build on top of our scalable cloud-native systems (AWS) including data flows, EC2 orchestration, containerized services, and compute clusters. • Experience with PyTorch or ML toolchains and familiarity with data workflows (Ray, Spark, or similar) • Excellent collaboration skills and ability to work across autonomy, ML, and robotics engineering domains
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