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Pomelkin/README.md

Hi, I'm Emelyan wave

Machine Learning Engineer (MLE) - Deep Learning, NLP, Generative AI


About me

  • I build ML systems end-to-end: data -> training -> evaluation -> MLOps -> deployment.
  • Core areas: Computer Vision (segmentation, detection, metric learning), NLP and LLM tooling (RAG, agents), real-time inference services.
  • I care about production quality: reproducibility, CI/CD, model registry, observability, and reliable serving.
  • Currently reading: "Machine Learning System Design" by Valerii Babushkin and Arseny Kravchenko.

Tech stack

  • Programming: Python (asyncio, multiprocessing), SQL
  • DL/ML: PyTorch, PyTorch Lightning, Transformers, TorchMetrics, scikit-learn, vLLM, Flash-Attention (pad-free), PyTorch Distributed (DP/TP/CP)
  • Data/Storage: PostgreSQL, S3, Polars, Qdrant
  • MLOps/DevOps: ClearML, DVC, LitServe, Docker, GitLab CI, GitHub Actions
  • Backend/Infra: FastAPI, Kafka, Redis, ZeroMQ, Nginx, Traefik

Contacts


Languages and tools

Python  PyTorch  FastAPI  Docker  PostgreSQL  Git 

Pinned Loading

  1. smiles-rag smiles-rag Public

    A rag pipeline for the case "RAG with additional information about the quality of embeddings"

    Python 2

  2. papper-ai/Papper-main papper-ai/Papper-main Public

    Main service

    Python 1

  3. papper-ai/Papper-graphs papper-ai/Papper-graphs Public

    Graph services

    Python 1

  4. RakePants/mvd-case-ai-kabanchiki RakePants/mvd-case-ai-kabanchiki Public

    Хакатон "Цифровой прорыв", кейс по определению носителей огнестрельного оружия // Leaders Of Digital hackathon, armed people recognition

    Jupyter Notebook 4

  5. RakePants/hack RakePants/hack Public

    Хакатон "Цифровой прорыв", кейс по классификации строительного мусора // Leaders of Digital hackathon, debris classification with Computer Vision

    Jupyter Notebook 3

  6. RakePants/biobase RakePants/biobase Public

    Информационная система "БАДы"

    JavaScript 1