Technical Product OwnerSep 2024 - Present

Continental Autonomous Mobility (now: Aumovio) Hybrid

• Technical Product Owner for 2 teams (21 engineers), leading both business and hands-on technical delivery of AI development and hardware integration in an autonomous driving product department.
• Introduced automation-first mindset: built automated release pipelines, dataset creation, data quality checking, and end-to-end testing of hardware and AI performance, reducing release turnaround by 67% (14 to 5 days) and doubling AI detection performance.
• Benchmarked various visual language models for automated quality checking of autolabeled image data and integrated the best-performing model into the data labeling pipeline, enhancing dataset quality, boosting CNN and overall product performance.
• Introduced a new LLM solution for hardware-side test case analysis and regular compliance reporting, reducing total time spent on these recurring tasks by 98%.
• Represented the product’s data and AI component in front of international customers, translating business needs into technical requirements and ensuring compliance with SOTIF, ASPICE 4.0, and EU AI Act.

Senior MLOps Engineer Aug 2023 - Sep 2024

Continental Autonomous Mobility (now: Aumovio) Hybrid

• Developed and productionized solutions that increased the MLOps maturity of AI projects across the company, via AI pipelines (continuous training, data/model drift), improved dependency management, and enhanced experiment tracking.
• Developed and led the adoption of Docker- and cluster-specific best practices (e.g., PyTorch DDP, mixed-precision training, GPU selection) to optimize GPU utilization for AI project teams on our Kubernetes cluster.
• Initiated, launched, and managed a corporation-wide MLOps knowledge center of best practices to regularly monitor and increase MLOps maturity of AI projects across the various company locations.
• Managed annual maintenance and upgrades of the company’s on-premises 100+ node Kubernetes cluster, collaborating with DevOps, infrastructure teams, and 300+ end users.

Machine Learning Engineer Sep 2021 - Aug 2023

EPAM Systems Hybrid

• Worked on the internal, machine learning tool for marketing planning of a leading fashion retailer to optimize their marketing strategy. Focus areas included developing and scheduling ETL pipelines in PySpark and Airflow, developing deep learning models for computer vision, writing data and model monitoring pipelines, and deploying and monitoring model performance.
• Participated in MLOps activities connected to the existing machine learning workflows, such as machine learning productionalization, model versioning, CI/CD workflows on Github and Gitlab, model and data drift monitoring, and automatic retraining via Airflow.
• Worked in agile teams and cooperated with business analysts, stakeholders, PO, DS lead, and project manager to identify epics and stories, define success criterias, and estimate timelines for the various features.
• Led the company's internal machine learning mentoring program for colleagues eager to start their career in data science and machine learning.

Production Team Lead Sep 2019 - Oct 2022

Innovative Language Learning Remote

• Led and coordinated a geographically dispersed, highly international QA team of 30+ people, overseeing proofreading of written and video content prior to publication.
• Planned and optimized weekly workloads, developed efficiency KPIs, and produced performance reports for upper management.
• Designed and executed onboarding and knowledge-transfer processes, updated company documentation, and enhanced transparency via biweekly QA/info sessions.

Machine Learning Engineer Oct 2019 - Sep 2021

Innovative Language Learning Remote

• Built a unified database of past customer interactions previously scattered across multiple sources, enabling centralized data access.
• Developed a semi-automated data labeling pipeline using unsupervised (K-means, DBSCAN) and semi-supervised (self-training classifier, label spreading) approaches.
• Designed and deployed AI natural language classifier prototypes to categorize incoming customer requests by department, technicality, linguistic nature, and content sensitivity.
• Leveraged AWS machine learning stack (Transcribe, Polly, Translate) to create an automated audio error detection tool.
• Implemented continuous model training to ensure AI systems adapt and improve over time, resulting in >$70k USD annual savings and 95% reduction in manual customer support handling.

MScBA Master in Management 2018 - 2019

Rotterdam School of Management, Erasmus University GPA: 4.0 / 4.0

One of Europe's leading business schools, renowned for its international focus and entrepreneurial spirit.

Key skills acquired: Strategic thinking, cross-cultural communication, financial analysis, leadership in diverse teams, and innovative problem-solving in global business contexts.

Extracurricular activities:

Exchange Semester 2018

University of Porto

Porto, Portugal

ERASMUS international exchange program focusing on advanced engineering and business studies.

Key skills acquired: Finance, project management, international teamwork, and Portuguese language proficiency through intensive study (many hours per week).

Mechatronics Engineering BSc 2014 - 2018

Budapest University of Technology and Economics GPA: 4.0 / 4.0

Hungary's leading technical university, renowned for engineering excellence and innovation in mechanical and electrical systems.

Key skills acquired: Technical expertise in mechanical and electrical systems, project management, interdisciplinary collaboration, analytical thinking, and hands-on engineering problem-solving.

Extracurricular activities: