I am a final-year B.Sc. Artificial Intelligence student at JKU Linz, currently combining research with hands-on production experience. I specialize in building scalable data pipelines, training and tuning machine learning models, and automating deployment processes with Docker and CI/CD. I enjoy working collaboratively in agile, multidisciplinary teams and strive to communicate clearly and contribute effectively. With practical experience in machine learning, MLOps, and software engineering, I've integrated complex systems such as MLflow with cloud-native tools, optimized real-time inference services, and enhanced operational monitoring. I am enthusiastic about continuous learning and adapting to new challenges in the AI and machine learning space.

MYKOLA LEN

I am a final-year B.Sc. Artificial Intelligence student at JKU Linz, currently combining research with hands-on production experience. I specialize in building scalable data pipelines, training and tuning machine learning models, and automating deployment processes with Docker and CI/CD. I enjoy working collaboratively in agile, multidisciplinary teams and strive to communicate clearly and contribute effectively. With practical experience in machine learning, MLOps, and software engineering, I've integrated complex systems such as MLflow with cloud-native tools, optimized real-time inference services, and enhanced operational monitoring. I am enthusiastic about continuous learning and adapting to new challenges in the AI and machine learning space.

Available to hire

I am a final-year B.Sc. Artificial Intelligence student at JKU Linz, currently combining research with hands-on production experience. I specialize in building scalable data pipelines, training and tuning machine learning models, and automating deployment processes with Docker and CI/CD. I enjoy working collaboratively in agile, multidisciplinary teams and strive to communicate clearly and contribute effectively.

With practical experience in machine learning, MLOps, and software engineering, I’ve integrated complex systems such as MLflow with cloud-native tools, optimized real-time inference services, and enhanced operational monitoring. I am enthusiastic about continuous learning and adapting to new challenges in the AI and machine learning space.

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Experience Level

Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate

Language

English
Advanced
German
Beginner

Work Experience

MLOps / DevOps Trainee at IT Outposts
June 30, 2025 - July 23, 2025
Integrated MLflow into GitHub Actions for streamlined Docker image builds and Kubernetes deployments with less than 5-minute rollback. Designed Helm charts for AWS EKS/GKE to standardize configurations, logging, and autoscaling. Enhanced real-time computer vision inference on Kubernetes, reducing API latency by 30% through customized autoscaling. Deployed Prometheus and Grafana dashboards for service and model monitoring, achieving 99.9% uptime and reducing MTTR by 40%. Automated S3 data versioning and ETL pipelines using Python and Boto3, cutting manual preparation time by 40%. Developed FinOps scripts to identify idle AWS resources and generate cost reports, saving pilot clients approximately 12% on monthly cloud spend.

Education

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Qualifications

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Industry Experience

Software & Internet, Professional Services, Computers & Electronics

Experience Level

Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate