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Achievement: Pull Shark

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FaizPalwala/README.md

Faiz Palwala

ML/Software Engineer. 4+ yrs enterprise distributed systems (Deloitte, 23M+ scale), MSc Advanced Computer Science (AI) @ Leeds.

Open Source & Core Contributions:

  • PyTorch Core: Contributor to upstream PyTorch (torch.nn.functional.nll_loss MPS forward migration on Apple Silicon, merged into pytorch:main).
  • SFHQ-VirtualID: Synthetic identity-conditioned benchmark for machine unlearning (750 identity clusters, 75k portraits, CC0 seeds, Slurm HPC array, published with DOI).
  • serverless-github-calendar: Zero-runtime-dependency GitHub contribution heatmap via GitHub Actions.
  • msc-project-core-implementation: Dual-head ResNet-18 evaluation framework for identity-level unlearning baselines.

Building:

  • Breadwinner: Local-first, zero-hallucination career engineering studio & AST compiler in Textual. Deterministic verification, offline Ollama/LM Studio support, and headless Chromium ATS PDF generation.
  • MLX Ternary: High-performance Apple Silicon runtime for 1.58-bit ternary language models with hardware vector dot product operations (dot(half4, half4)) and Split-K parallelization.
  • GraphContext MCP: Structural AST and dependency graph engine for AI coding assistants (Proprietary commercial product).

1,100+ contributions in the last year. Writing & systems essays: faizpalwala.tech

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  1. breadwinner breadwinner Public template

    Local-first, zero-hallucination resume tailoring studio & compiler built in Textual. Deterministic verification, offline Ollama/LM Studio support, and headless Chromium ATS PDF generation.

    Python 1

  2. serverless-github-calendar serverless-github-calendar Public

    Zero-runtime-dependency GitHub contribution heatmap. Server-first data pipeline via GitHub Actions, no third-party proxy in the request path.

    TypeScript 3

  3. virtual-id-gen virtual-id-gen Public

    Synthetic identity-conditioned face datasets for machine unlearning — 750 identities, Bench 224×224 + Raw 1024×1024 (75k portraits), InstantID + Juggernaut-XL-v9.

    Python

  4. msc-project-core-implementation msc-project-core-implementation Public

    Machine Unlearning Methods (Baselines and State-of-the-art), helper functions for experimental analysis

    Python