ML Ops Engineer

📋 Description

• Design, scale, and maintain high-performance MLOps and LLMOps infrastructure for an AI-infused
• Collaborate with Data Scientists, ML Engineers, and Cloud Infra teams to streamline training
• Ensure GPU utilisation, reliability, and cost-efficiency across cloud environments

🎯 Requirements

• Hands-on production experience in DevOps, SRE, or Platform Engineering for AI/ML infra
• Proven track record deploying and operationalising ML models and LLMs in cloud-native production
• Experience managing GPU infrastructure and HPC environments
• Advanced proficiency in Kubernetes, Docker, Helm, KubeFlow; service meshes (e.g., Istio)
• Terraform, Ansible, GitHub Actions, ArgoCD, or Jenkins
• Experience with vLLM, Ray, MLflow, LangChain / LangSmith, DeepSpeed, or Hugging Face TGI

🎁 Benefits

• DEIB focused culture and opportunities to grow within a global team
• Competitive benefits and career development
• Work on cutting-edge AI/ML infrastructure and platform engineering