GPU Optimization Engineer (ML Infrastructure)

Kadence Talent is partnered with an AI x Quantum start-up, looking for a GPU Optimization/ML Infrastructure Engineer to make it easy for researchers to run compute-heavy workloads at scale.You'll sit between ML and infrastructure, helping scientists move from local experiments to scalable GPU-backed systems across cloud environments.What You'll DoEnable GPU access and scaling across AWS/GCPBuild simple systems to run and manage compute-heavy workloadsImprove speed, reliability, and cost-efficiency of experimentsHelp transition workflows from Modal ? native cloudSupport research using tools like Qiskit and PennyLaneReduce friction & make infra invisible and easy to useWhat We're Looking ForExperience with AWS or GCP (compute, basic networking)Familiarity with GPU workloads (PyTorch, CUDA, etc.)Strong Python skillsExperience with Docker (Kubernetes is a plus)Comfortable working in a hands-on, startup environmentNice to HaveML/AI infrastructure or training pipelinesDistributed compute (Ray, Dask, Spark, etc.)Experience supporting researchers or data scientistsWhy This RoleWork at the intersection of quantum + ML + infrastructureBuild systems from scratch - high ownership, high impactTurn unused compute into real research outputLocation: This is an on-site role in Mountain View, CACompensation: $250k - $280k+, plus equity