Machine Learning Engineer

As a Machine Learning Engineer at OPSWAT, you will join a dynamic team dedicated to developing advanced AI-driven cybersecurity solutions that protect critical infrastructure worldwide. This role involves designing, building, and deploying machine learning models to address real-world cybersecurity challenges, contributing to OPSWAT's mission of safeguarding complex networks and ensuring compliance.

Your primary responsibilities will include training, testing, and optimizing machine learning models for cybersecurity and malware detection use cases. You will experiment with various model architectures, perform data exploration and feature engineering on large datasets, and design evaluation pipelines to assess model performance. Additionally, you will collaborate with data engineers and threat researchers to enhance data quality and support the deployment and monitoring of models in production environments.

The ideal candidate will possess a degree in Computer Science, Mathematics, Engineering, AI, or a related field, along with a solid understanding of machine learning algorithms and model evaluation techniques. Proficiency in Python and experience with ML libraries such as scikit-learn, TensorFlow, or PyTorch are essential. Familiarity with data preprocessing, feature engineering, and working with real-world datasets is required. Experience with cloud platforms, particularly AWS, and knowledge of MLOps practices are advantageous. Strong problem-solving skills and the ability to communicate findings effectively within cross-functional teams are also important.

OPSWAT offers a collaborative and innovative work environment, providing opportunities for professional growth and development. Employees benefit from working on impactful projects that contribute to protecting organizations from cyber threats.