Padmi

Performance verification

BangalorePosted 2 months ago
Software QualityNew gradFull Time
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Job Title: Performance Verification Engineer Job Summary We are seeking a Performance Verification Engineer to validate and optimize system performance across hardware, firmware, and software components. The role involves designing performance test strategies, analyzing bottlenecks, and ensuring that products meet defined performance targets under various workloads. Key Responsibilities Define and execute performance verification plans for system-level validation. Develop benchmarks, workloads, and stress tests to evaluate performance metrics such as latency, throughput, power, and scalability. Analyze performance bottlenecks and provide root cause insights. Collaborate with architecture, design, and software teams to improve system efficiency. Automate performance test frameworks and reporting tools. Perform performance characterization across different configurations and environments. Validate performance against specifications and customer requirements. Generate detailed reports, dashboards, and documentation. Work with regression testing teams to ensure sustained performance across releases. Tune system parameters (memory, CPU, IO, network) for optimal performance. Required Skills & Qualifications Bachelor's/Master's degree in Computer Science, Electronics, Electrical Engineering, or related field. Strong understanding of computer architecture, OS concepts, and system performance metrics. Experience with performance benchmarking tools (e.g., SPEC, Iometer, FIO, JMeter, etc.). Programming/scripting skills in Python, C/C++, or Shell. Knowledge of Linux/Unix environments. Familiarity with profiling and debugging tools (e.g., perf, VTune, gprof). Understanding of memory hierarchy, caching, and multi-threading concepts. Strong analytical and problem-solving abilities. Preferred Qualifications Experience in SoC/CPU/GPU performance validation. Knowledge of virtualization, cloud workloads, or data center performance testing. Exposure to power-performance optimization. Experience with CI/CD pipelines and automation frameworks. Familiarity with AI/ML workload performance (optional but valued).

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