Senior LLMOps Engineer: AI Training & Inference Platform Lead

PatSnap; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

PatSnap in Singapore seeks a Senior LLMOps Engineer with strong software engineering and infrastructure skills to lead initiatives for model training, inference services, and training data management. You will own and operate training platforms, deployment workflows, and platform automation while collaborating with AI/ML, security, and product teams to accelerate AI adoption across the company.

You will join a hands-on team responsible for scaling training workloads, optimizing GPU and compute

Qualifications

• Proficient in Python programming and building platform services.
• Experience with Linux, Kubernetes, GPU resource management, and observability tools.
• Hands-on experience with model training, inference infrastructure, and deployment of open-source models.

Responsibilities

• Lead development of model training platforms and workflows, including scheduling and troubleshooting.
• Build and operate model inference capabilities with centralized access and management.
• Manage training data storage, versioning, quality checks, and access control.
• Develop automation for lifecycle management, deployment, and monitoring of models and services.
• Improve resource utilization, reliability, and cost of training/inference workloads.
• Participate in 24/6 on-call rotations to resolve incidents and improve platforms.
• Collaborate with AI/ML, engineering, and security teams to enable AI adoption.

Skills

Python

Kubernetes

Linux

CI/CD

Observability

GPU management

Open-source deployment

SRE / MLOps

Tools

Docker

Terraform

Airflow

Job description

PatSnap in Singapore seeks a Senior LLMOps Engineer with strong software engineering and infrastructure skills to lead initiatives for model training, inference services, and training data management. You will own and operate training platforms, deployment workflows, and platform automation while collaborating with AI/ML, security, and product teams to accelerate AI adoption across the company.

You will join a hands-on team responsible for scaling training workloads, optimizing GPU and compute