Mikhail Rozhkov
Technical Product Manager, AI MLOps at Nebius AI
Amsterdam, North Holland, Netherlands
Summary
🤩
Rockstar🎓
Top SchoolMikhail Rozhkov is a Technical Product Manager specializing in AI MLOps with 11 years of experience building production-ready ML systems and developer-facing tools. Currently at Nebius, he focuses on serverless AI platforms that simplify running real-world ML workloads, drawing on deep hands-on experience as a Solutions ML Engineer at Iterative where he helped onboard the company’s first paid customers and built custom integrations across industries. He co-founded Machine Learning REPA to deliver training, consulting, and practical integrations (DVC, Evidently, Airflow, Argo, etc.), and contributes to open-source projects like Evidently—adding a Streamlit integration that showcases his ability to make observability tools more accessible. Mikhail blends product leadership, teaching (visiting lecturer on ML system design), and applied engineering to move teams from prototype to production, and his background in finance and a PhD-focused competencies study gives him a rare mix of technical, business, and organizational insight. Based in Amsterdam, he thrives at the intersection of developer ergonomics, ML reliability, and measurable business impact.
11 years of coding experience
6 years of employment as a software developer
PhD Competencies and Performance Management, PhD Competencies and Performance Management at The Hong Kong Polytechnic UniversitySpecialist Finance management, Specialist Finance management at The Moscow State University of Economics, Statistics and Informatics (MESI)Specialist (Master) Marketing, Specialist (Master) Marketing at Amur State University
English, Chinese, French, German
Stackoverflow
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0reached
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Github Skills (13)
pandas10
streamlit10
python10
data-science10
performance-monitoring9
machine-learning9
jupyter-notebook9
uptime-monitoring9
process-monitoring9
data-monitoring9
monitoring9
data-quality8
html8
Programming languages (8)
Github contributions (5)
evidentlyai/evidently
Dec 2020 - Sep 2023
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:5 PRs, 1 comment in 2 years 10 months
Contributions summary:Mikhail implemented a Streamlit dashboard integration example, demonstrating the ability to incorporate Evidently's functionalities into a user-friendly interface. They updated the examples/integrations/readme.md file to include the new integration, and modified code style and removed redundant files. The changes involve significant code modifications and the integration of a new visualization tool.
ml-modelspythonmonitordiscordjupyter-notebook
mlrepa/automate-ml-with-dvc
Jun 2019 - Apr 2021
Contributions:24 commits, 1 push, 1 branch in 1 year 10 months
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