Senior MLOps Engineer

Join Us in Transforming Cybersecurity

ThreatModeler

Come join us and together, well shape the future of cybersecurity!

Senior MLOps Engineer

managing, and scaling AI/ML-driven services in production environments.

The ideal candidate will have deep hands-on experience with cloud infrastructure, containerization,

CI/CD pipelines, security best practices, and scalable AI system design.

Key Responsibilities:

• Design, build, and manage end-to-end MLOps pipelines.
• Deploy and manage AI/ML services using Docker and Kubernetes.
• Automate model lifecycle management including versioning and rollback.
• Ensure scalability, reliability, and fault tolerance.
• Implement CI/CD pipelines for ML workflows.
• Monitor model performance, data drift, and system health.
• Collaborate with Data Scientists, Backend Engineers, and DevOps teams.
• Enforce security best practices across infrastructure.
• Optimize infrastructure cost and performance.
• Maintain documentation and operational runbooks.

Required Skills & Qualifications:

• 5+ years of experience in MLOps, DevOps, or ML Engineering.
• Strong experience with Docker, Kubernetes, and cloud platforms (AWS/Azure/GCP).
• Experience with Infrastructure as Code (Terraform/CloudFormation).
• Strong understanding of scalable distributed systems.

Security & Scalability:

• Knowledge of IAM, RBAC, secrets management, and network security.
• Experience with secure ML deployments and compliance standards.

Monitoring & Observability:

• Experience with Prometheus, Grafana, ELK, or cloud monitoring tools.
• Understanding of model monitoring and drift detection.

Good to Have:

• Experience with GenAI/LLM deployments.
• Familiarity with MLflow, Feature Stores, and Data Pipelines.