AI/ML Engineer 20 Positions

Company Description: Seceon Inc. delivers a next-generation, AI-powered cybersecurity platform designed to help enterprises, MSPs, and MSSPs detect, respond to, and remediate cyber threats in real time while reducing dependence on multiple siloed security tools.

Its unified platform brings together SIEM, SOAR, UEBA, EDR, NDR, Threat Intelligence, Vulnerability Management, and Compliance within a single scalable, multi-tenant solution. Seceon's technology can process more than 10 million security events per second, enabling organizations to manage comprehensive security operations through a centralized dashboard.

Through aiSecurity360, Seceon helps organizations streamline continuous compliance with leading security and regulatory frameworks, including NIST, ISO, HIPAA, PCI-DSS, CMMC, and NIS2.

Organizations choose Seceon to improve threat detection and response, gain greater visibility across logs, endpoints, networks, and identities, simplify security operations, and reduce the overall cost and complexity of managing cybersecurity.

Role Description The AI/ML Engineer role at Seceon Inc. is a full-time remote position focused on designing, implementing, and optimizing machine learning and AI models for advanced threat detection and automated response. Day-to-day responsibilities include developing and testing algorithms for pattern recognition, building and training neural networks, and collaborating with cybersecurity experts to translate security challenges into ML solutions. The role involves working with large-scale event data, performing statistical analysis, and improving model accuracy, scalability, and performance in production environments. AI/ML Engineers will also participate in code reviews, documentation, and cross-functional initiatives to enhance the capabilities of Seceon's unified cybersecurity platform across multiple tenants and high-throughput systems. With 20 openings available, team members will contribute directly to core product innovation and the future of AI-driven cybersecurity.

Qualifications

• Strong foundation in Computer Science and Algorithms, including data structures, complexity analysis, and software engineering principles.
• Hands-on experience with Pattern Recognition and Neural Networks for classification, anomaly detection, and time-series or event-based data.
• Proficiency in Statistics for model evaluation, hypothesis testing, and performance metrics in large-scale ML systems.
• Experience with modern ML/AI frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and programming languages such as Python or Java.
• Background in distributed systems, data pipelines, or streaming platforms (e.g., Kafka, Spark) for high-volume data processing is highly beneficial.
• Familiarity with cybersecurity concepts, threat detection, or security operations tools is a strong plus.
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field, or equivalent practical experience.
• Ability to work effectively in a remote, collaborative environment, communicate clearly, and manage priorities in a fast-paced setting.