1 month ago
Budapest, HungaryMid Level
Responsibilities
- Train and fine-tune models using curated datasets and run 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, false negatives, drift, and edge cases, and use findings to improve datasets and training.
- Own dataset pipelines, labeling workflows, and data quality processes.
- 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 accuracy, precision/recall tradeoffs, drift, and edge-case analysis.
- Ability to work against defined acceptance criteria and production constraints.
Benefits
- Ongoing training and development opportunities for professional growth.
- Collaborative, innovative, mission-driven cybersecurity environment.
- Team-building activities and social events in a fun, dynamic workplace.
- Based in OPSWAT’s newly opening Budapest office.
Tech Stack
Categories
Data EngineeringML Engineering
About OPSWAT
OPSWAT builds cybersecurity software for critical infrastructure, delivering malware prevention, content disarm and reconstruction, secure file transfer, and device access control across IT, OT, and ICS environments. It sells enterprise software and SaaS platforms to public- and private-sector organizations worldwide. Founded in 2002 and headquartered in Tampa, Florida, the privately held company is used in regulated industries such as energy, government, and finance.