Principal MLOps Engineer (Cortex)
Core
Architecting high-performance MLOps and LLMOps platforms to enable Data Scientists and Security Researchers to build, train, and deploy advanced AI systems including SLMs and agentic workflows.
Role type
Principal MLOps Engineer (ML Platforms & Infrastructure)
Builds
Scalable compute platforms, automated ML/LLM lifecycle pipelines, and production serving infrastructure for LLMs/SLMs.
Domain
Cybersecurity, AI/ML Infrastructure, Cloud Computing
Deliverable
production ML models | infrastructure
Required skills
Distributed GPU training optimization, MLOps/LLMOps pipeline architecture, LLM/SLM serving architecture, Cloud infrastructure (GCP/AWS/Azure), Python (ML infrastructure), CI/CD automation, Deep Learning fundamentals
Preferred skills
GCP ecosystem expertise, Data science background, Cybersecurity domain knowledge
Technologies
PyTorch, DeepSpeed, Megatron-LM, GitLab CI, GitHub Actions, Claude, Gemini, MCPs
Responsibilities
Design and optimize infrastructure for distributed training and fine-tuning of LLMs/SLMs; Architect automated pipelines for continuous training and deployment; Own serving architecture for LLMs/SLMs balancing latency and throughput; Establish observability systems for model performance and data drift; Partner with data scientists and security researchers to productize model architectures.
Seniority
Principal, hands-on IC