Job Description
📋 Description Architect ML platform strategy across data pipelines, training infra, and serving layers. Build production-grade, low-latency ML serving with lifecycle tooling. Define the agentic stack and bridge platform with product needs. Mentor engineers and drive architectural excellence across teams. Operate as a technical force multiplier for AI infrastructure. Lead strategic initiatives to enable faster, reliable AI capabilities. 🎯 Requirements 7+ years on ML Platform/MLOps with deep tooling knowledge. Proven ownership of core ML platform components (Spark, Ray, MLFlow, Kubeflow, Metaflow). Built and operated high-throughput agentic stack (data infra, context store, orchestration). Strong Python expertise for batch and online service frameworks. Experience designing online vs offline inference systems and tradeoffs. Ability to provide ML infra perspective in cross-team AI strategy discussions. 🎁 Benefits Health, wellness, and equity benefits. ERGs and community programs to support inclusive culture.
