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Tier-1 brand, Bangalore location and generic title increase competition, while niche GPU/AI validation reduces it.
Highly specialized GPU and AI-cluster validation skills limit candidate transferability across industries.
Explicit years, mandatory GPU/distributed AI validation, Python, automation, and release-gate requirements make shortlisting strict.
Own end-to-end validation, testing, and release qualification for AI cluster solutions and Cisco network-switch integrations.
Develop and execute test plans, automation, and acceptance criteria for GPU/distributed AI systems, including performance profiling and bottleneck analysis.
Drive defect triage, collect evidence, manage release readiness, and produce benchmark and acceptance reports.
Bachelor's degree with 2+ years related experience, or Master's degree with 0+ years related experience.
Experience building and executing end-to-end validation for GPU or distributed AI systems.
Skills in test strategy, automation, Python, Linux, performance analysis, defect triage, and translating system requirements into tests and release gates.
Experience with technical writing and cross-functional communication.
Experienced in GPU platforms (e.g., NVIDIA CVIS/NVIS), AI cluster validation, and network storage testing.
Familiar with benchmark engineering, workload modeling, CI-based testing, and release management for complex distributed systems.
Comfortable working with Cisco networking and AI cluster reference architectures in a technical leadership or senior engineering role.