
Cybersecurity solutions for critical infrastructure protection
OPSWAT, headquartered in Tampa, Florida, specializes in cybersecurity solutions for critical infrastructure, including the protection of 98% of U.S. nuclear power facilities. Their products, such as MetaDefender and OESIS Framework, focus on malware prevention and secure data transfer, ensuring comp...
Employees enjoy competitive salaries, comprehensive health benefits, a flexible remote work policy, and generous PTO. OPSWAT also offers equity option...
OPSWAT fosters a culture of security and innovation, emphasizing the importance of protecting critical infrastructure. The company values transparency...

OPSWAT • Veszprém, Veszprém, Hungary
OPSWAT is seeking a Machine Learning Operations Engineer to develop and deploy AI-driven cybersecurity solutions. You'll work with technologies like Python, AWS, and Docker to build reliable ML pipelines. This role requires experience in machine learning and operations.
You have a strong background in machine learning operations, with experience in building and deploying ML models in production environments. Your expertise in Python allows you to create efficient and scalable ML pipelines that support data scientists in delivering innovative solutions. You are familiar with cloud platforms like AWS, enabling you to leverage cloud resources for model training and deployment. Your knowledge of containerization technologies such as Docker and orchestration tools like Kubernetes helps you manage and scale ML applications effectively. You understand the importance of collaboration and communication, working closely with cross-functional teams to ensure seamless integration of ML solutions into existing systems. You are committed to continuous learning and professional development, always seeking to enhance your skills and knowledge in the rapidly evolving field of machine learning.
Experience with cybersecurity applications or critical infrastructure is a plus, as it aligns with OPSWAT's mission to protect complex networks. Familiarity with data engineering practices and tools will further enhance your ability to support data scientists in their work. A proactive approach to problem-solving and a passion for innovation will help you thrive in this role.
As a Machine Learning Operations Engineer at OPSWAT, you will be responsible for developing and maintaining ML pipelines that facilitate the deployment of AI-driven cybersecurity solutions. You will collaborate with data scientists to understand their requirements and translate them into scalable and reliable ML workflows. Your role will involve optimizing model performance and ensuring that models are efficiently integrated into production systems. You will also monitor and troubleshoot ML applications, addressing any issues that arise to maintain high availability and performance. Additionally, you will contribute to the design and implementation of infrastructure that supports the deployment of machine learning models, leveraging cloud technologies to enhance scalability and reliability.
You will participate in code reviews and contribute to best practices in ML operations, fostering a culture of continuous improvement within the team. Your insights will help shape the future of OPSWAT's AI-driven solutions, making a significant impact on the security of critical infrastructure worldwide. You will have the opportunity to work in a modern office environment in Veszprém, collaborating with talented professionals who share your commitment to innovation and excellence.
At OPSWAT, we provide a supportive and collaborative work environment where your contributions are valued. We offer opportunities for professional development through training and mentoring, helping you grow your skills and advance your career. Our commitment to innovation means you will work with cutting-edge technologies and be part of a team that is making a real difference in the world of cybersecurity. We encourage you to apply even if your experience doesn't match every requirement, as we believe in the potential of diverse backgrounds and perspectives.
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