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Software Engineer, Planner Reasoning, ML Infrastructure

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The role

Develop novel ways to inspect, understand, filter, improve and curate data for ML training and evaluation.
Build data tooling and infrastructure to unblock experimentation and productionalize ML solutions.
Collaborate closely with partner teams such as perception, research, simulation, and evaluation.
Stay up-to-date with the latest data-driven approaches and prototype, develop and deploy these novel solutions to open-ended problems.
Leverage offboard ML training and data pipelines infrastructure and analyze large datasets to derive insights.
Contribute to scalable evaluation workflows and build robust metrics for ML models.

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