Senior MLOps Engineer
Core
Architect and operate systems for training, fine-tuning, deploying, and monitoring NLP and LLM models at scale to power AI security and governance workflows.
Role type
Senior MLOps Engineer
Builds
ML infrastructure, tooling, and operational foundations for NLP and LLM training, evaluation, and deployment
Domain
AI Security, Governance, Cloud Infrastructure, NLP, LLMs (via careerplan.io/jobs/3A-005-FD-062-senior-mlops-engineer-at-noma-security)
Deliverable
production ML models
Required skills
Python, transformer architectures, NLP frameworks (PyTorch, HuggingFace), LLM deployment and scaling, GPU optimization, distributed training, Kubernetes, cloud platforms, CI/CD for ML
Preferred skills
Internal ML platform operations, LLM evaluation frameworks, model observability, security implications in ML pipelines, multi-model orchestration, vector DBs
Technologies
PyTorch, HuggingFace, SageMaker, Vertex AI, Kubernetes (EKS/GKE/AKS), Helm, Terraform
Responsibilities
Design and maintain pipelines for training, fine-tuning, evaluating, and deploying NLP and LLM models; Implement automated CI/CD workflows for ML models including benchmarking and testing; Select and optimize serving frameworks for low-latency, high-throughput inference; Manage training environments, experiment tracking, model registries, and distributed training systems; Monitor and optimize production models for performance, cost efficiency, and observability
Seniority
Senior, hands-on IC
