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Tier-1 brand and Bangalore metro increase competition, but niche CPU+ML co-design skills reduce candidate pool.
Highly specialized CPU architecture and ML kernel skills limit transferability across industries.
Requires 8+ years, mandatory low-level C/C++ and CPU+ML kernel expertise, making filters very strict.
Own CPU software–hardware co-design for next-generation QMX architectures focusing on ML workloads, including workload characterization, simulation, kernel optimization, and performance bottleneck analysis.
Develop and optimize highly efficient ML kernels and libraries (e.g., GEMM, convolution, attention) integrated with ML frameworks to enable ML workloads on CPU platforms.
Collaborate closely with CPU architecture and design teams to provide data-driven insights and influence future CPU architectural enhancements based on real workload performance.
Bachelor's degree in Engineering, Information Systems, Computer Science, or related field with 8+ years of software engineering or related experience OR Master's degree with 7+ years OR PhD with 6+ years.
4+ years of experience programming in C/C++ (mandatory).
Work Experience Required: Minimum 6-8 years software engineering or related experience depending on degree level.
Experience with performance profiling, benchmarking, and optimization.
Experienced in CPU architecture and systems programming with strong machine learning fundamentals, focusing on ML workload performance optimization.
Proficient in low-level software development including kernel development, SIMD/vectorization, and memory/cache optimization for CPU-centric ML workloads.
Able to transform real ML workload analysis into actionable architectural insights influencing future CPU designs, especially for vector/SIMD extensions like QMX.