Hello! This is the SOC Analytics team.
We define current methods for building corporate network security monitoring, establish controls based on specific methodologies, and also build controls based on the internal needs of the Information Security Department. We determine the necessity of logging for systems, services, and devices. Additionally, we are involved in monitoring external information sources whose data may impact the security of the IT infrastructure, as well as improve existing information security controls by verifying the applicability and relevance of such messages. The team is responsible for providing informational support for incident investigation procedures and responding to alerts from continuously operating security monitoring components. We are developing TI and ML capabilities.
And now we are looking for a Senior Information Security Engineer (ML).
You will
- Develop and evolve LLM services and data pipelines in Python.
- Design and implement agent logic: tool orchestration, step planning, context processing.
- Integrate the LLM agent into the team's IRP/SIEM processes.
- Create information security monitoring based on ML models (anomaly detection, classifiers, graph models).
- Write integrations for external ML infrastructure into our SIEM to work with ML monitoring.
- Implement MLOps tasks: setting up and supporting CI/CD, pipeline automation, release cycles.
- Deploy services and large projects into production.
- Participate in code reviews, writing tests and documentation.
- Study new ML/LLM agent technologies and their application in team projects.
We value
- 4+ years of experience as an ML engineer.
- Proficiency in Python (async/await, typing, code architecture).
- Experience with LLMs: OpenAI-compatible APIs, prompt engineering, RAG.
- Experience in developing and training classical ML models (classification, anomaly detection, graph models).
- Backend development experience: gRPC/protobuf, REST.
- Experience deploying services and large projects into production environments (k8s, CI/CD, object storage).
- Understanding of the code delivery process to production (Git, CI/CD).
- Experience working with logs and metrics of running services.
Will be a plus
- Experience building LLM agents and integrating them into processes.
- Familiarity with SIEM, IRP solutions.
- Experience in evaluating the quality of ML/LLM systems: metrics, test sets, LLM-as-a-judge.
- Experience with Airflow/Dagster or similar tools for automating calculations.
