Dr. Vladyslav Libov
Verified Expert in Engineering
Artificial Intelligence Developer
Hamburg, Germany
Toptal member since July 22, 2025
Vladyslav is a senior consultant specializing in artificial intelligence, machine learning operations (MLOps), cloud technologies, software development, and quantum computing. He has a broad academic and industry experience, with projects at large financial institutions, top consultancy firms, rail operators, and other enterprise companies. Vladyslav has a strong background in artificial intelligence and machine learning, probability theory and statistics, software development, and physics.
Portfolio
Experience
- Physics - 20 years
- Python 3 - 15 years
- AI Model Training - 10 years
- Artificial Intelligence (AI) - 10 years
- Azure - 6 years
- Large Language Models (LLMs) - 5 years
- Machine Learning Operations (MLOps) - 4 years
- Cloud - 4 years
Preferred Environment
Linux, Bash, Python 3, Azure, Kubernetes, LangChain, PyTorch, Python, Docker, Pytest, FastAPI, REST APIs, PostgreSQL, Research
The most amazing...
...solution I've developed is an ML-based credit rating system for the largest development bank in Germany.
Work Experience
Senior AI Consultant
D-fine
- Trained, deployed, and maintained production ML models using MLOps practices at a major railway company, resulting in substantial operational cost savings.
- Designed and implemented an ML-based credit risk system for a large German development bank managing a multibillion loan portfolio.
- Developed a Kubernetes-based platform for risk analysis and ML operations for a real-estate bank in Germany, securing €25 million in project funding.
- Conducted internal and external training sessions on AI and MLOps.
Scientist | Project Leader
University of Hamburg
- Coordinated the installation and commissioning of a complex scientific facility with a budget of €5 million.
- Led the technical design of a particle accelerator facility.
- Authored research papers in high-profile journals.
Research Scientist
German Electron Synchrotron
- Designed a complex accelerator facility, which was used as a basis for actual construction.
- Performed detailed analytical calculations and Monte-Carlo Simulations to assess the feasibility and fine-tune the design.
- Supervised PhD and Master students, coordinated international teams.
Research Scientist (PhD Student)
DESY
- Developed a C++ and Python-based framework for extensive data analysis.
- Performed a rigorous analysis of a large dataset from a particle physics experiment.
- Lectured at the University of Hamburg (theoretical physics).
Experience
Machine Learning Model for Credit Risk Assessment
AI-based Model for Online Game Matching and Player Stylometry
Machine Learning Engineering
• GitOps with fluxCD
• Monitoring stack (Prometheus and Grafana)
• Service Mesh (Istio)
• Storage (S3-like, minio)
• MLOps tools, specifically end-to-end pipeline tools, Kubeflow, and Flyte
Then I implemented the training pipelines in close collaboration with the customer, I.e I was tranlating their experiments into fully-fledged MLOps processes, from collecting data through training to pushing the models to MLFlow.
This also required implementing more classical DEV-OPS Pipelines to build and deploy the necessary images serving particular use-cases.
The use cases studied are predictive maintenance, demand forecasting, smart assistants, feedback systems, peak spotting, and delay forecasting.
Data Science
The result was a measurement with the best precision achieved to date.
Particle Accelerator Design
• Performed feasibility studies using advanced analytical calculations, Monte-Carlo simulations, and particle codes.
Development of AI Agents for Automotive Manufacturers
LLM-based Application for an Education Company
Education
PhD in Physics
University of Hamburg - Hamburg, Germany
Skills
Libraries/APIs
PyTorch, Scikit-learn, Gradio, REST APIs, SciPy, TensorFlow, OpenAI API, OpenCV, Keras
Tools
Git, GitHub, ChatGPT, AutoML, Pytest, You Only Look Once (YOLO), Azure Machine Learning, Makefile, MATLAB, Mathematica
Languages
Python 3, Python, C++, R, SAS, Bash
Frameworks
Agentic Frameworks
Paradigms
Automation, Role-based Access Control (RBAC)
Platforms
Kubernetes, Docker, Azure AI Search, Azure Functions, Azure, Amazon Web Services (AWS), Microsoft, Google Cloud Platform (GCP), NVIDIA CUDA, Vertex AI, Linux, Kubeflow
Storage
Data Pipelines, PostgreSQL, Azure SQL Databases, Microsoft SQL Server, Azure Blobs
Industry Expertise
Project Management
Other
Artificial Intelligence (AI), Large Language Models (LLMs), Machine Learning Operations (MLOps), Machine Learning, AI Model Training, Physics, Data Analysis, Retrieval-augmented Generation (RAG), Agentic AI, Generative Artificial Intelligence (GenAI), Data Science, Deep Learning, Transformers, Vision Transformer (ViT), Convolutional Neural Networks (CNNs), Neural Networks, OpenAI, Small Language Models (SLMs), CI/CD Pipelines, Research, Prompt Engineering, Architecture, APIs, Communication, Linear Regression, Random Forests, Computer Vision, Microsoft Azure, Data Engineering, Predictive Modeling, Cloud Infrastructure, Image Processing, Cloud, LangChain, Leadership, AI Agents, OpenAI Agent Builder, Langflow, Firecrawl, Algorithms, AI Algorithms, API Integration, Player Matching, Matching Systems, Fine-tuning, FastAPI, Equity, Finance, Vector Databases, Blob Storage, MLflow, AI Integration, Open-source LLMs, Bayesian Statistics, GPU Computing, Quantization, Identity & Access Management (IAM), Cloud Security, Distributed Systems, Consulting, Transportation & Logistics, Computer Vision Algorithms, Software Development, Hardware Development, Simulations, Monte Carlo Simulations, Monte Carlo, Design of Experiments (DOE), Hardware, Hardware Design, Experimental Research, fluxcd, Infrastructure as Code (IaC), Statistics, Probability Theory, Glean, Azure Blob Storage, Scalability, Security, LLM Agents
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