ML Ops Engineer
A company is looking for an ML Ops Engineer to architect and implement efficient ML inference pipelines for large language models. Responsibilities: Design and implement high-performance inference pipelines Optimize model serving for throughput, latency, and cost across different workloads Collaborate with research and product teams to integrate inference into real-world applications Qualifications: Deep experience developing and tuning LLM inference frameworks (e.g. vLLM) Experience with cloud infrastructure (AWS, GCP, Azure) and Kubernetes Passion for AI and practical ML systems Experience building, deploying, and operating highly available, scalable, distributed cloud services
A company is looking for an ML Ops Engineer to architect and implement efficient ML inference pipelines for large language models.
Responsibilities:
Design and implement high-performance inference pipelines
Optimize model serving for throughput, latency, and cost across different workloads
Collaborate with research and product teams to integrate inference into real-world applications
Qualifications:
Deep experience developing and tuning LLM inference frameworks (e.g. vLLM)
Experience with cloud infrastructure (AWS, GCP, Azure) and Kubernetes
Passion for AI and practical ML systems
Experience building, deploying, and operating highly available, scalable, distributed cloud services
