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Open nowPosted 40 days ago

Machine Learning Data Builder

Workable (global search)108,016 open roles

Where
Budapest, Hungary
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Your applicationOpen nowMachine Learning Data BuilderWorkable (global search) · Budapest, Hungary

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The clock on this job

Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 7 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.0%30 days
This job: posted 40 days ago

Workable (global search) median: 7 days open

The posting

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.

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
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