Software engineer working close to the metal on next-generation AI accelerator hardware. I build and optimize low-level compute kernels, profile and benchmark tensor operations, and hunt bottlenecks across the stack to drive device throughput — and own end-to-end model tracing and validation plus the tooling and infrastructure around it.
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- Software engineering for a leading AI silicon company’s accelerator stack — developing and optimizing the software that runs on next-generation AI chips. -
- Work as part of an element-wise operations team — contributing kernel development, code review, and CI health for unary/binary element-wise ops. -
- Author and optimize low-level compute kernels with broad data-type coverage (fp32, bf16, int32, uint8/16/32) and hardware-specific instruction-level work verified against ISA documentation. -
- Own end-to-end model tracing and validation with sweeps — reconstructing real model operation traces from a database and validating them against generated sweep tests for exact-match coverage. -
- Profile and benchmark kernels with the device profiler, tracking kernel execution time and diagnosing per-core load imbalance to guide optimization. -
- Maintain performance-tracking automation and daily/weekly reporting pipelines that flag regressions against historical baselines and correlate them to commits. -
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- Developed and maintained a smart attendance system using face-recognition technology with database integration. -
- Built an ESD tester with database-backed logging for real-time test workflows. -
- Worked on computer-vision algorithms, biometric authentication, and real-time data processing. -
+ aswincloud.com / github.com/Aswincloud / linkedin.com/in/aswin4122001
+ Software engineer working close to the metal on next-generation AI accelerator hardware. I build and optimize low-level compute kernels, profile and benchmark tensor operations, and hunt bottlenecks across the stack to drive device throughput — and own end-to-end model tracing and validation plus the tooling and infrastructure around it.
+ +Experience
+-
+
- Software engineering for a leading AI silicon company’s accelerator stack — developing and optimizing the software that runs on next-generation AI chips. +
- Work as part of an element-wise operations team — contributing kernel development, code review, and CI health for unary/binary element-wise ops. +
- Author and optimize low-level compute kernels with broad data-type coverage (fp32, bf16, int32, uint8/16/32) and hardware-specific instruction-level work verified against ISA documentation. +
- Own end-to-end model tracing and validation with sweeps — reconstructing real model operation traces from a database and validating them against generated sweep tests for exact-match coverage. +
- Profile and benchmark kernels with the device profiler, tracking kernel execution time and diagnosing per-core load imbalance to guide optimization. +
- Maintain performance-tracking automation and daily/weekly reporting pipelines that flag regressions against historical baselines and correlate them to commits. +
-
+
- Developed and maintained a smart attendance system using face-recognition technology with database integration. +
- Built an ESD tester with database-backed logging for real-time test workflows. +
- Worked on computer-vision algorithms, biometric authentication, and real-time data processing. +
Projects
ttnn-eltwise-performance.aswincloud.com
Skills
+Education
+2019 – 2023 • CGPA 8.5 / 10