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趨勢科技 - 全球雲端資安領航者 / 全亞洲最大軟體公司 / 企業版圖橫跨五大洲 / 趨勢全球研發基地在台灣
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About the Role
We are building a production-grade, GPU-accelerated LLM serving platform that powers multiple AI products at enterprise scale. You will be responsible for designing, building, and operating the infrastructure that serves large language models — from raw Kubernetes cluster management to multi-GPU inference optimization and autoscaling.
Required Qualifications
Model Serving & Inference
- Operate multi-model LLM serving infrastructure
- Tune autoscaling policies to balance GPU cost and latency SLAs
Kubernetes & GPU Infrastructure
- Operate production K8s clusters with NVIDIA GPU nodes
- Handle GPU node lifecycle: NVIDIA driver setup
Infrastructure as Code
- Write and maintain Terraform/Terragrunt modules for AWS/GCP cloud
- Package platform components and model deployments as Helm charts
- Manage multi-environment configurations
Observability & Performance
- Maintain monitoring stack: Prometheus, Grafana,
- Build dashboards for GPU utilization, KV cache occupancy, TTFT/ITL latency, and cost per token
- Set up alerting for SLA violations and OOM events
Bonus Skills
These are not required, but candidates with these skills will stand out.
- LoRA / PEFT fine-tuning workflows
- MLflow for experiment tracking, model registry, and automated adapter deployment
- Experience building LoRA adapter CI/CD pipelines (training → registry → serving)
- Experience with alternative inference frameworks such as SGLang or NVIDIA NIM, including deep Parameter Tuning for Continuous Batching, KV Cache management, and Speculative Decoding.
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連結智慧 守護世界 --- Connected Intelligence for Securing a Connected World
Skills Required
- Operate multi-model large language model serving infrastructure
- Tune autoscaling policies to balance GPU costs and latency service-level agreements
- Operate production Kubernetes clusters with NVIDIA GPU nodes
- Manage GPU node lifecycle, including NVIDIA driver setup
- Write and maintain Terraform and Terragrunt modules for AWS and GCP
- Package platform components and model deployments as Helm charts
- Manage multi-environment infrastructure configurations
- Maintain Prometheus and Grafana monitoring infrastructure
- Build dashboards for GPU utilization, KV cache occupancy, TTFT/ITL latency, and cost per token
- Configure alerting for SLA violations and out-of-memory events
- Implement LoRA and PEFT fine-tuning workflows
- Use MLflow for experiment tracking, model registry, and automated adapter deployment
- Build LoRA adapter CI/CD pipelines
- Use SGLang or NVIDIA NIM and tune continuous batching, KV cache management, and speculative decoding
What We Do
We’re a global cybersecurity leader, helping to make the world safe for exchanging digital information. Fueled by decades of security expertise, global threat research, and continuous innovation, our cybersecurity platform protects hundreds of thousands of organizations and millions of individuals across clouds, networks, devices, and endpoints. As a leader in cloud and enterprise cybersecurity, our platform delivers a powerful range of advanced threat defense techniques optimized for environments like AWS, Microsoft, and Google, and central visibility for better, faster detection and response. Our global threat research team delivers unparalleled intelligence and insights that power our cybersecurity platform and help protect organizations around the world from 100s of millions of threats daily. We have 7,000 employees across 65 countries, singularly focused on security and passionate about making the world a safer and better place. We enable organizations to simplify and secure their connected world. Trend Micro’s “Trenders” are passionate about doing the right thing to make the world a safer and better place.
