Requirements:- Python programming using classic scientific stack (numpy, pandas, scipy, scikit-learn) + some visualization tools like matplotlib, plotly or other similar libraries- Experience with machine learning algorithms and ideally numerical optimization algorithms- Experience and/or understanding of Tensorflow or Pytorch. Ideally experience with huggingface transformers- Proficient with SQL- Understanding of fundamental concepts of OOP and functional programming to create maintainable and
Requirements:- Python programming using classic scientific stack (numpy, pandas, scipy, scikit-learn) + some visualization tools like matplotlib, plotly or other similar libraries- Experience with machine learning algorithms and ideally numerical optimization algorithms- Experience and/or understanding of Tensorflow or Pytorch. Ideally experience with huggingface transformers- Proficient with SQL- Understanding of fundamental concepts of OOP and functional programming to create maintainable and scalable code- git managementPreferred:- Experience with Numba or at least understanding of its usage and challenges during implementation- Experience with creation of backend microservices with Python (ideally FastAPI)- Experience and/or strong understanding of LLMs + RAG systems (vector DBs, semantic + keyword search and reranking, knowledge base preparation and parsing, prompting techniques)- Basic bash skillsResponsibilities:- Write and optimize code using Python, pandas, scipy, numba, SQL etc.- Solve non-linear optimization problems (in task scheduling and allocation space) using genetic algorithms, local search and other methods.- Creation of LLM-based RAG assistants with combinations of both client's knowledge base and general knowledge possessed by model (data preparation, semantic and hybrid search engines, LLM grounding)