Work across many different aspects of machine learning infrastructure and modeling. Support new modeling techniques and products for changing infrastructure (training and serving). Prototype new infrastructure, automation, workflows, and tooling. Analyze and debug performance, and make improvements. Improve robustness, reliability, usability of infrastructure. Collaborate closely with other members of our team and partners to build systems that take advantage of and integrate seamlessly across our ecosystem. Engage with modeling teams to explore pain points and novel use cases. Research emerging technology and make trade-off decisions on immediate wins vs longer-term stability.
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