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OPSWAT

Protects critical infrastructure from malware

Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeBudapest, HungaryNo salary listedIn-person

About the Job

Requirements

  • At least 2 years of machine learning engineering or applied data science experience.
  • Strong Python skills and hands-on experience with modern model training and fine-tuning workflows.
  • Experience with structured model evaluation, including accuracy, precision/recall tradeoffs, drift, and edge-case analysis.
  • Ability to work against defined acceptance criteria and production constraints.

Responsibilities

  • Train and fine-tune models against curated datasets, and run systematic hyperparameter and architecture experiments.
  • Build and maintain model evaluation suites, including regression tests for model behavior and benchmark tracking across model versions.
  • Analyze model failures, including false positives and false negatives, and translate findings into dataset or training improvements.
  • Package models with documentation, benchmarks, and reproducible evaluation results for handoff to the Engine team.
  • Contribute to internal tooling for experiment tracking and model comparison.

About the Company

OPSWAT

Protects critical infrastructure from malware

OPSWAT provides cybersecurity solutions that protect critical infrastructure from malware and zero-day attacks by focusing on threat prevention and secure data transfer. Its products secure files and devices at all stages—entry, exit, and rest—ensuring secure access and safe data exchange. The company differentiates itself through deep specialization in high-risk sectors like energy, finance, and government, and by achieving widespread trust (notably 98% of U.S. nuclear power facilities) for its compliance-driven approach. Its goal is to help organizations maintain secure, compliant operations and minimize the risk of cyber compromise while keeping systems productive.

Company size
1,001-5,000
Company stage
Growth Equity (Venture Capital)
Total funding
$125M
Headquarters
Tampa, FL
Founded
2002

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