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Tier-1 brand and Bangalore metro increase competition, though role's niche CPU+ML focus limits applicant pool.
Highly specialized CPU architecture and ML kernel skills are not easily transferable across industries.
Mandatory low-level systems, C/C++, and ML/kernel expertise create stringent technical filters.
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Own CPU software–hardware co-design focusing on machine learning workloads and system-level performance optimization for next-generation QMX CPU architectures.
Lead workload characterization, simulation, profiling, kernel optimization, and architectural feedback to improve ML workload execution efficiency on CPU platforms.
Develop and optimize ML kernels and libraries, collaborate with CPU architecture teams to influence design enhancements, and benchmark performance across hardware generations.
Bachelor's degree in Engineering, Information Systems, Computer Science, or related field with 3+ years software engineering experience OR Master's degree with 2+ years OR PhD with 1+ year.
2+ years academic or work experience programming in C/C++ (mandatory).
Experience with performance profiling, benchmarking, and optimization required.
Work Experience Required: 1+ to 3+ years software engineering or related work experience based on degree level.
Experienced in CPU architecture, systems programming, and machine learning fundamentals with practical exposure to low-level kernel development and CPU performance optimization.
Skilled in simulation tools such as QEMU and profiling tooling, with ability to analyze bottlenecks across CPU pipelines, memory hierarchies, and instruction utilization.
Able to collaborate effectively with architecture and design teams to provide data-driven insights and influence next-generation CPU design features specifically for ML workloads.