Machine Learning Engineer

• Design, build, and operate next-generation systems that run large-scale batch inference workloads (from minutes to multi-day jobs).
• Build developer-friendly APIs, SDKs, and CLIs that let researchers and engineers submit and manage batch inference jobs with minimal effort.
• Design, implement, and operate distributed services that package, schedule, execute, and monitor batch inference workflows at massive scale.
• Instrument the platform for reliability, debuggability, observability, and cost control; define SLOs and share an equitable on-call rotation.
• Partner with content and studio ML practitioners to support model inference needs and workflows.
• Foster a culture of engineering excellence through design reviews, mentorship, and candid, constructive feedback.

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