Senior MLOps Engineer
Core
Design, build, and own the infrastructure and workflows for machine learning and LLM-powered systems, creating a reliable path from experimentation to production.
Role type
Senior MLOps Engineer (hands-on IC)
Builds
MLOps platform infrastructure, CI/CD pipelines, model registries, automated deployment, and scalable inference systems for cloud, on-prem, and air-gapped environments.
Domain
AI/ML engineering, Cloud Infrastructure, DevOps
Deliverable
infrastructure
Required skills
Linux, Docker, Kubernetes, Terraform, Ansible, CI/CD, Python, Bash, GPU infrastructure, Cloud platforms (AWS/Azure/GCP), Networking, Security, ML tooling, Workflow orchestration
Preferred skills
RAG/agent frameworks, Vector DBs, Model optimization/quantization
Technologies
Ollama, vLLM, Prometheus, Grafana, GitHub Actions, Azure DevOps, MLflow, Kubeflow, Airflow, Kafka, MCP
Responsibilities
Design and operate MLOps platform infrastructure and LLM inference pipelines; Build automated CI/CD pipelines and monitoring systems; Establish MLOps/DevOps standards and reusable templates; Provision containerized workloads and manage GPU-enabled hardware; Troubleshoot platform incidents and maintain operational resilience.
Seniority
Senior, hands-on IC
