About

We are developing and scaling a network service and looking for an experienced AI/ML & Data Science engineer to integrate advanced intelligence into our infrastructure. Your role will be to design and implement ML-based solutions that improve security, reliability, and performance across our distributed servers. Key Responsibilities: Build ML models for anomaly detection and suspicious traffic identification. Develop algorithms for routing optimization and load distribution based on real-time metrics. Create predictive models for infrastructure performance and failure prevention. Research and apply methods to reduce risks of traffic analysis and strengthen data confidentiality. Collaborate with engineers to integrate models into production with minimal latency. Provide monitoring, analytics, and reporting tools to support decision-making. Requirements: Proven experience in Machine Learning / Data Science, with projects in anomaly detection, predictive modeling, or optimization. Strong knowledge of network traffic analysis, time-series modeling, and real-time data processing. Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.). Familiarity with network protocols, distributed systems, and server performance metrics. Experience with real-time ML pipelines and model optimization. Understanding of security and privacy considerations in networked systems. Nice to have: Background in cybersecurity or large-scale networking systems. Experience deploying ML models in production (Docker, Kubernetes, microservices). Knowledge of advanced traffic obfuscation or adversarial ML techniques. What we offer: Long-term collaboration on a growing network product. Opportunity to design and implement cutting-edge ML features with real-world impact. Flexible remote work and competitive compensation.