Senior Software Engineer, ML Ops & Infrastructure
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The role
Design and implement scalable ML infrastructure to train and deploy deep learning models on a real-time robotic stack.
Optimize data loading and training throughput across 1000+ GPU jobs and build distributed data pipelines for robotics data.
Develop APIs and tooling to enable researchers to apply machine learning techniques, with opportunities to contribute to open-source models.
Orchestrate compute resources (GPUs/TPUs) and workflows on GKE to reduce cost and latency in model development, across cloud and on-prem environments.
Build tools for model understanding, evaluation, reliability, and traceability across the ML lifecycle.
Collaborate across cross-functional teams to translate research into production-grade ML-powered robotics capabilities.
Optimize data loading and training throughput across 1000+ GPU jobs and build distributed data pipelines for robotics data.
Develop APIs and tooling to enable researchers to apply machine learning techniques, with opportunities to contribute to open-source models.
Orchestrate compute resources (GPUs/TPUs) and workflows on GKE to reduce cost and latency in model development, across cloud and on-prem environments.
Build tools for model understanding, evaluation, reliability, and traceability across the ML lifecycle.
Collaborate across cross-functional teams to translate research into production-grade ML-powered robotics capabilities.
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