Staff ML Serving Platform Engineer
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The role
Line 1: This role targets building the next generation of ML model serving with a focus on reliability, efficiency, and cost-aware scaling.
Line 2: Design and implement real-time inference systems capable of handling high QPS with strict latency SLOs.
Line 3: Operationalize modern inference optimizations—caching, batching, quantization, and memory-efficient techniques—across a diverse hardware fleet.
Line 4: Create platform-wide abstractions to enable broad reuse across workloads and improve developer velocity, observability, and maintainability.
Line 5: Collaborate with ML engineers, infrastructure teams, and OSS communities, contributing back where valuable and influencing the roadmap.
Line 6: Ideal candidates have 8+ years building large-scale serving systems and a track record of mentoring peers and delivering high-quality, scalable software.
Line 2: Design and implement real-time inference systems capable of handling high QPS with strict latency SLOs.
Line 3: Operationalize modern inference optimizations—caching, batching, quantization, and memory-efficient techniques—across a diverse hardware fleet.
Line 4: Create platform-wide abstractions to enable broad reuse across workloads and improve developer velocity, observability, and maintainability.
Line 5: Collaborate with ML engineers, infrastructure teams, and OSS communities, contributing back where valuable and influencing the roadmap.
Line 6: Ideal candidates have 8+ years building large-scale serving systems and a track record of mentoring peers and delivering high-quality, scalable software.
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