Andrei Politov

• Training /tuning, production deployment Gen.AI / LLM up to 30B+ models wrt scalability. Research and development: NLP (Multiling. Translation, NER) applications and methods; Building and scaling LLM infrastructure. • MLOps for NLP/ VC applications: Python, C++, TensorFlow, PyTorch, CUDA, vLLM, Unitest, Numpy, Pandas, HPC, MlFlow, Docker, Kubernetes, Gitlab/Github CI/CD, DVC, FastAPI, Hydra, AWS(Sagemaker), Azure. Scrum • Head of the junior development team. Lead hackathons, ML and MLOps training

• Development and optimisation of product ML (CV) applications with Python, PyTorch, Docker; Research on containerisation of NLP applications; Benchmarking of HPC infrastructure with Python, Unitest, Docker, MPI, C++ • Developed of the documentation system for the HPC center: Gitlab CI/CD, Docker, Python, FastAPI

• Developed an Approach to Self-Supervised Object Localisation through Deep Learning Based Classification • Research in the area of Self-Supervised learning; Solving of Computer Vision tasks for image data. Image processing; Database management; Parallelisation of computations; Development of visualization methods Technologies: Python, PyTorch, OpenCV, Scikit-, NumPy, Pandas, Pytest

Planning and management of research and engineering projects. - Planning and implementation of research projects using appropriate questions and research methods - Digitization of production processes - Work with the project plans. Managing project progress; communicating with the project team; evaluating the project risk; controlling the budget.

- Mathematical modelling of processes and equipment for critical process points - Research and development in the energy, chemical industry and environmental science - Process chain programming - Digitization of processes in the manufacture - Creating work algorithms and equipment for energy, chemical industries and environmental science - Project management, quality control and management of manufacturers, author's support

“Computational Modelling and Simulation” Master program (Informatik) Computational and mathematical foundations of Computational Modeling with emphasis on Computer Science. Focus: Machine learning (2 projects); Data visualization; GPU programming; HPC.

Intensive German course​

Foundations of Mathematical Modelling and applications of Energy and Resource Saving Technologies Master thesis: Research and development of centrifugal extractors for recycling processes -Graduated with honours. A university academic grant for young scientists(2014 - 2015)

-Planning, Technical and Economic Analysis of Enterprise Performance; -Fundamentals of Enterpreneurial Activity and Corporate Economics; -Accounting and Audit; -Quality managment.

Mathematical and physical foundations of mechanical engineering and chemical engineering A university academic grant (2006 - 2010) - Advanced Mathematics - Mechanical Engineering - Physic - Computer science - Process engineering - Advanced math for mathematical modelling of technological processes