Requirements: English
Company: GLOBAL CLEARANCE SOLUTIONS POLAND sp. z o.o.
Region: Bialystok , Podlaskie Voivodeship
technologies-expected : Python technologies-optional : TensorFlow PyTorch scikit-learn about-project : This role focuses on evolving and expanding the remote mathematical modeling tool for system identification. The candidate will analyze advanced academic literature and existing solutions to determine the most effective ML/AI algorithms for both supervised and unsupervised tasks - ranging from automated PCA and regression to cutting-edge classifiers (including transformers, GANs, and time series modelling). They will design, implement, and validate these algorithms in a live testing platform. responsibilities : Systems Identification & Mathematical Modeling: Develop algorithms for system identification using labelled and unlabeled data, identifying correlations, dependencies, and optimal model parameters. Implement advanced methods such as automated Principal Component Analysis (PCA), ensemble regression, and deep learning classifiers (e.g., transformers, GANs, etc.). Algorithm Research & Integration: Evaluate academic literature and state-of-the-art ML/AI frameworks to discern which algorithms provide the best performance for the data modeling tool. Integrate hyperparameter optimization techniques (e.g. Bayesian optimization) and evaluate simulation platforms to compare algorithm performance in near real time. Customize loss functions, metrics, benchmarking and architecture. Development & Testing: Extend the existing Python-based modeling tool using libraries such as TensorFlow, PyTorch, scikit-learn, and/or other competitive frameworks. Create an intuitive live testing dashboard to compare modeling outcomes, iterate easily, and visualize performance metrics. Collaboration & Documentation: Collaborate with cross-functional teams to refine requirements and document algorithms, ensuring reproducibility and scalability. requirements-expected : Strong background in machine learning, statistical modeling, and data science, including proficiency with Pythons ML ecosystem. Expertise in system identification techniques and experience with advanced ML models (deep learning, transformers, GANs, time series forecasting). Experience with hyperparameter optimization methods and simulation-based evaluation of algorithm performance. Familiarity with research methodologies and academic literature in ML/AI, enabling the adoption of cutting-edge techniques. Analytical: A highly analytical and inquisitive mind that thrives on deciphering complex data relationships and innovating new solutions. offered : Work in an experienced international team Business trip opportunites Participation in unique research and development projects Well-equipped research laboratory Stable employment in an international group