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Compiler Engineer
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Assessing your cultural and operational fit
IBM
Data Scientist
June 16, 2026 – Present
ppc-mlir-llvm-project
December 15, 2025 – December 16, 2025
ppc-mlir-llvm-project — GitHub repository
View Projectllvm-ppc-mma-mlir
November 22, 2025 – November 22, 2025
The LLVM Project is a collection of modular and reusable compiler and toolchain technologies. This repo is for PowerPC MMA research work in MLIR.
View Projectpowerpc-mlir-investigation
November 14, 2025 – December 17, 2025
powerpc-mlir-investigation — GitHub repository
View Projectpowerpc-mlir-research
November 5, 2025 – November 5, 2025
Research on optimizing code using PowerPC MMA
View ProjectLearnAdvancedCompilers
November 12, 2023 – November 13, 2023
Learning advanced compiler optimizations using LLVM
View ProjectBaseStationAssistedD2D
April 11, 2017 – May 1, 2017
Base Station Assisted D2D communication
View ProjectDeviceToDeviceVideoTransferLTE
February 12, 2017 – February 12, 2017
Base-Station Assisted D2D communications for wirelss video Networks
View ProjectRust-Graph-Algorithms
May 24, 2016 – May 24, 2016
parallel Graph Algorithms implemented in RUST language
View ProjectCooperative-Relay-Selection
March 8, 2016 – March 8, 2016
Co-Operative Relay Selection Using Optimal Stopping Rule
View ProjectParallel-Sparse-Multiplication
March 8, 2016 – March 8, 2016
Parallel Sparse Multiplication Using C++
View ProjectCultural Fit Analysis
The candidate's projects are heavily focused on low-level systems, compilers, and parallel computing, which are not directly aligned with a typical Data Scientist role. While there is an 'IBM Data Scientist' role listed, it is marked as current with a future start date, suggesting limited practical experience in the target domain. The project diversity is high within the compiler/systems domain but lacks breadth in data science specific areas like machine learning, statistical modeling, or data engineering. This indicates a potential mismatch with the target role's typical requirements.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's projects are primarily technical and do not provide insight into collaboration, communication, or problem-solving approaches in a team setting.