Responsibilities
- Train and fine-tune models using curated datasets while running systematic hyperparameter and architecture experiments.
- Build and maintain model evaluation suites, regression tests, 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 Engine team handoff.
- Contribute to internal tooling for experiment tracking and model comparison.
Requirements
- At least 2 years of ML 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 precision/recall tradeoffs, drift, and edge-case analysis.
- Ability to work against defined acceptance criteria and production constraints.
Benefits
- Based in OPSWAT’s newly opening Budapest office.
- Ongoing training and development opportunities.
- Collaborative, mission-driven cybersecurity environment.
- Team-building activities and social events.
- Equal opportunity employer committed to a diverse and inclusive workplace.
Tech Stack
Categories
About OPSWAT
OPSWAT protects critical infrastructure. Our goal is to eliminate malware and zero-day attacks. We believe that every file and every device pose a threat. Threats must be addressed at all locations at all times—at entry, at exit, and at rest. Our products focus on threat prevention and process creation for secure data transfer and safe device access. The result is productive systems that minimize risk of compromise. That’s why 98% of U.S. nuclear power facilities trust OPSWAT for cybersecurity and compliance. OPSWAT. Trust no file. Trust no device. www.opswat.com Visit us on Twitter, Facebook, Instagram, and YouTube. http://www.twitter.com/opswat http://www.facebook.com/opswat https://www.instagram.com/opswat https://www.youtube.com/user/opswat1