Skip to main content
Loading
loadingbar
Loading, Please wait..!!

Head of GPU Cloud

  • Head of GPU Cloud job type Posted on: Nov 06, 2026
  • Head of GPU Cloud experience level Confidential
  • Head of GPU Cloud employment type El Paso, Texas
  • Head of GPU Cloud employment type Onsite
  • Head of GPU Cloud salary Full-time

Point Apply Here APPLY LATER

Curious about compensation?

Explore the historical salary trends, average pay, and estimated compensation for Head of GPU Cloud roles in Texas.

View Salary Guide →

Job Title :

Head of GPU Cloud

Job Type :

Full-Time

Job Location :

El Paso Texas United States

Remote :

No

Jobcon Logo Job Description :

Head of GPU Cloud About the Company Building software foundation for next-generation accelerated computing platform for large-scale AI infrastructure IndustryComputer Software TypePrivately Held About the Role The Company is in search of a Head of GPU Cloud to spearhead the engineering team dedicated to the development of a next-generation accelerated computing platform. The successful candidate will be instrumental in defining the architecture and operating model for large-scale AI inference services, with a direct impact on GPU utilization, platform economics, and customer experience. This role demands a leader with a strong technical background in software engineering, particularly in the areas of cloud platforms, distributed infrastructure, and HPC. The Head of GPU Cloud will be responsible for shaping the platform architecture, production inference, and engineering strategy, and must have a proven track record in leading engineering teams and making critical technical decisions. Key responsibilities for the Head of GPU Cloud include building and scaling the engineering organization, setting the architecture for efficient AI workload management, and leading the optimization of production model serving. The ideal candidate will have at least 12 years of software engineering experience, with a focus on large-scale model inference and a deep understanding of technologies such as vLLM, TensorRT LLM, and TGI. Advanced knowledge of Kubernetes, containerized infrastructure, and practical experience with GPU memory behavior and high-bandwidth networking is essential. The role also requires a leader with strong technical and leadership judgment, capable of balancing performance, reliability, security, and customer experience across multidisciplinary teams. Experience in GPU cloud, AI infrastructure, and a track record of improving accelerator utilization and compute economics are highly valued. Functions Engineering

Jobcon Logo Position Details

Posted:

Nov 06, 2026

Reference Number:

12517_1609c36208cc51229117751ba6cb04d347caaa2a7c5a774787da4259a628fcc6

Employment:

Full-time

City:

El Paso

Job Origin:

APPCAST_CPC

Share this job:

  • linkedin

Jobcon Logo
A job sourcing event
In Dallas Fort Worth
Aug 19, 2017 9am-6pm
All job seekers welcome!

Head of GPU Cloud    Apply

Click on the below icons to share this job to Linkedin, Twitter!

Head of GPU Cloud About the Company Building software foundation for next-generation accelerated computing platform for large-scale AI infrastructure IndustryComputer Software TypePrivately Held About the Role The Company is in search of a Head of GPU Cloud to spearhead the engineering team dedicated to the development of a next-generation accelerated computing platform. The successful candidate will be instrumental in defining the architecture and operating model for large-scale AI inference services, with a direct impact on GPU utilization, platform economics, and customer experience. This role demands a leader with a strong technical background in software engineering, particularly in the areas of cloud platforms, distributed infrastructure, and HPC. The Head of GPU Cloud will be responsible for shaping the platform architecture, production inference, and engineering strategy, and must have a proven track record in leading engineering teams and making critical technical decisions. Key responsibilities for the Head of GPU Cloud include building and scaling the engineering organization, setting the architecture for efficient AI workload management, and leading the optimization of production model serving. The ideal candidate will have at least 12 years of software engineering experience, with a focus on large-scale model inference and a deep understanding of technologies such as vLLM, TensorRT LLM, and TGI. Advanced knowledge of Kubernetes, containerized infrastructure, and practical experience with GPU memory behavior and high-bandwidth networking is essential. The role also requires a leader with strong technical and leadership judgment, capable of balancing performance, reliability, security, and customer experience across multidisciplinary teams. Experience in GPU cloud, AI infrastructure, and a track record of improving accelerator utilization and compute economics are highly valued. Functions Engineering

Loading
Please wait..!!