Mikhail M.

AI/ML Engineer | Data Scientist | Computational Chemistry

AI/ML Engineer and Data Scientist with a PhD in engineering sciences, combining extensive experience in machine learning, scientific data analysis, computational chemistry, and industrial R&D. I build machine learning and AI solutions for scientific, engineering, and commercial projects — from data analysis and predictive modeling to production-ready software and research workflows. My background is moderately unusual: before moving deeply into AI and machine learning, I spent many years working in applied research and technology development. This included chemical and technological processes, analytical methods, experimental data, software, patents, and peer-reviewed research. This combination is particularly useful when the problem is not simply "train a model" but requires understanding the data and the underlying process. Areas I work in include: - Machine learning and deep learning - Data science and predictive modeling - Large language models and AI applications - Scientific and experimental data analysis - Chemometrics and multivariate statistics - Computational chemistry - Spectroscopy, chromatography, and mass spectrometry data - Process modeling and optimization - Custom algorithms and scientific software - Data pipelines, automation, and ML workflows I primarily work with Python (NumPy, SciPy, scikit-learn, PyTorch, TensorFlow, Keras), as well as R, MATLAB, and cloud platforms. I choose the tools according to the problem rather than forcing a particular technology onto it. Projects can range from a focused data analysis or prototype to a complete ML workflow or a piece of research software. I am comfortable starting with an existing specification, investigating an unclear problem, or helping define the technical approach when the requirements are still evolving. My experience includes work with research organizations, industrial projects, and individual clients. My Upwork history also reflects long-term freelance work and a 100% Job Success Score. If your project involves AI, machine learning, complex scientific data, or a problem where domain knowledge matters as much as the algorithm, feel free to get in touch.