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.

As a Machine Learning Engineer 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.

You Will Have the Opportunity to

• 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

Requirements

• 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

Benefits

• Stable, growing international company background with an exceptional customer group 
• Opportunity to improve your professional skills 
• The newest technology environment 
• Language course and opportunity for active recreation – kettlebell, football and office massage 
• Attractive working environment – nice office full of accessories (fruits every day, coffee, breakfast, tea etc.) 
• Regular team events and Happy Hour activities