Machine Learning Data Builder

Our client is a global leader in cybersecurity for IT, OT, and ICS critical infrastructure. Their end-to-end platform gives enterprises and public sector organizations the critical advantage they need to protect complex networks, secure devices, and meet compliance requirements.

Over the past 20 years, a consistent commitment to innovative technology has earned the trust of more than 1,700 organizations, governments, and institutions worldwide — cementing the company's role in protecting the world's critical infrastructure and securing our way of life.

On their behalf, we are looking for ML Data Builder ready to contribute to that mission.

s a Machine Learning Data Builder you will own the data foundation the team runs on: dataset pipelines, labeling workflows, and data quality. Model quality is bottlenecked by data quality; this role removes that bottleneck. We've had a strong presence in Veszprém for over a decade, and we're now expanding into Budapest, this role is based in our newly opening Budapest office, right at the start of that growth.

• Build and maintain dataset ingestion, cleaning, and versioning pipelines (training, validation, and held-out evaluation sets)
• Design and operate labeling workflows, including quality control and inter-annotator agreement tracking
• Own dataset testing: coverage analysis, class balance, leakage detection, dataset documentation
• Manage dataset versioning and lineage so every model release traces back to exact training data
• Partner with data science and product engineering teams on data-sharing boundaries and formats

• 3+ years data engineering experience; strong Python and SQL
• Experience with data versioning tools (DVC, LakeFS, or similar) and pipeline orchestration (Airflow, Dagster, or similar)
• Understanding of ML-specific data concerns: train/test leakage, label noise, distribution shift
• Rigor in documentation and reproducibility