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Medium — Tier-1 Bangalore role but senior niche AI validation reduces applicant density.
High — requires deep compiler/runtime, accelerator, and AI validation expertise, limiting cross-industry transferability.
High — explicit 10+ years, specialized AI validation experience and mandatory C++/Python requirements.
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Define and lead the end-to-end validation strategy for an AI software stack on a next-generation AI computational storage platform.
Own the functional, runtime, and performance validation of neural network operators, compute kernels, graph-level execution, and AI workloads.
Lead cross-team validation efforts and mentor engineers on automation, performance validation, and debugging to ensure correctness, scalability, reliability, and performance.
10+ years of experience in AI software validation, systems software validation, or performance engineering.
Strong expertise in C++ and Python programming with Object-Oriented Programming fundamentals.
Deep knowledge of AI/ML execution pipelines, neural network operators, deep learning frameworks (PyTorch preferred), runtime architectures, scheduling systems, and memory hierarchy.
Experience validating large-scale AI workloads, building automated test/benchmarking frameworks, and performing root-cause analysis.
Experienced in leading end-to-end validation across compiler, runtime, kernel, and hardware teams in AI software environments.
Strong technical leader skilled in defining validation strategies, quality gates, and mentoring engineering teams towards automation and performance improvements.
Familiar with AI software stack components including MLIR, XLA, TensorRT, multi-device execution, and accelerator platforms (GPU, NPU, FPGA).