The role focuses on building and extending an agentic framework for on-robot workflows, creating benchmarks for robotic task evaluation, integrating work with simulation and on-robot deployment, and profiling performance bottlenecks in resource-constrained Linux environments. Candidates should be pursuing a Master's or PhD in a relevant field, have prior software engineering experience, and understand PyTorch and modern AI architectures such as LLMs, VLMs, or reinforcement learning.
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