Senior MLOps Engineer
- Practices
- CI/CD, LLMOps, MLOps
Responsibilities Design, build, and maintain scalable MLOps and LLMOps infrastructure on GCP. Develop and manage ML pipelines using M
Lflow, ZenML, Kubeflow, and Vertex AI Pipelines . Manage containerized environments using Docker and Kubernetes . Automate infrastructure provisioning with Terraform .
Build and maintain CI/CD pipelines for ML and GenAI applications using GitHub Actions. Design and orchestrate LLM and agentic workflows using LangGraph. Implement evaluation frameworks for LLMs, RAG systems, and AI agents .
Monitor ML and GenAI applications, including model performance, drift, tracing, and observability . Develop scalable data processing pipelines using Dataflow and Apache Beam . Collaborate with Data Scientists and Engineering teams to deliver production-ready AI solutions .
Provide technical guidance and promote MLOps and LLMOps best practices across the team.
Strong professional experience in MLOps / LLMOps . Hands-on experience with GCP , particularly Vertex AI, Dataflow, and BigQuery. Strong knowledge of Terraform, Docker, and Kubernetes . Experience with Kubeflow, Argo Workflows, M
Lflow, ZenML, and/or Vertex AI Pipelines . Strong Python and Bash skills. Experience building CI/CD pipelines for ML and/or GenAI applications.
Practical experience with Generative AI and LLM applications . Experience with LangGraph or similar AI orchestration frameworks. Knowledge of LLM evaluation, RAG evaluation, model monitoring, and drift detection .
Familiarity w