ML Ops Engineer

Job summary

Ana*** is seeking a ML Ops Engineer to join their Platform Engineering team, focusing on designing, scaling, and maintaining high-performance MLOps and LLMOps infrastructure.

Qualifications

• Hands-on production experience in DevOps, SRE, or Platform Engineering
• Proven track record of deploying and operationalising machine learning models
• Experience managing compute-intensive GPU infrastructure
• Advanced proficiency in Kubernetes, Docker, Helm, KubeFlow
• Hands-on experience with Terraform, Ansible, GitHub Actions, ArgoCD, Jenkins
• Experience with vLLM, Ray, MLflow, LangChain, DeepSpeed, Hugging Face TGI
• Solid background in AWS, GCP, Azure, and GPU cost optimisation techniques
• Strong skills in Python, Bash, or Go; knowledge of Linux kernel tuning

Responsibilities

• Provision and manage cloud-native AI/ML infrastructure
• Automate core platform infrastructure using Infrastructure as Code tools
• Optimise GPU compute workloads and storage
• Build and maintain CI/CD and MLOps pipelines
• Deploy Large Language Models and generative AI workloads
• Enable automated model validation and monitoring
• Monitor and optimise cloud spend across GPU/CPU clusters
• Implement auto-scaling strategies and dynamic resource allocation
• Establish benchmarking and telemetry for AI models
• Implement end-to-end observability using various tools

Skills

Relocation