I'm a AI & Software Engineer with a passion for building scalable, data-driven systems. I specialize in backend architecture, data pipelines, and functional programming β designing fast, reliable software for complex problems across e-commerce, telecom, and algorithmic trading.
With a BEng in Artificial Intelligence and an ongoing MSc in High Performance Computing at the University of Edinburgh, I bring a strong academic foundation to practical engineering. My current thesis explores neuroevolution and multi-agent deep reinforcement learning in the StarCraft II environment β combining reinforcement learning, large scale parallelism, and agent-oriented design.
Whether it's optimizing a dataflow or architecting clean services, I focus on solutions that are correct by design, scalable, and built to last.
- π§ Languages: Python, Elixir, C/Cython, Haskell, Elm
- π οΈ Frameworks: Yesod, Phoenix/Ash, Elm Land
- π Data & ML: Dask, Pandas, PyTorch, SQL/NoSQL
- βοΈ Cloud & Infra: AWS, Docker, Kafka, RabbitMQ
- βοΈ HPC & Parallelism: MPI, OpenMP, CUDA, OpenSHMEM
off_broadway_websocket
β Off-broadway producer for ingesting WebSocket streams in Elixirasync-websocket-pool
β WebSocket pool manager for async data feedsgeminex
β Elixir wrapper for Gemini exchange's REST API
- πΌ LinkedIn
- βοΈ michal.polit@monadic.eu
π Always happy to connect over backend design, data engineering, or functional programming.