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Read everything carefully. The requirements and screening questions are critical and if not answered correctly and satisfactorily will result in auto-rejection and waste of your time. Work from Home. This is a full-time role. If you plan to do 2 or more jobs at the same time or want to do this part time, that won't work for us. In that case please do not apply as it will get auto-rejected Note - this job requires working late night India time until 4 AM to overlap with USA working times. Do not apply if this timing doesn't work Salary depends on experience and current verifiable (paychecks) compensation. Junior candidates with 2 years experience are suitable About Qubrid AI Qubrid AI is building a full-stack AI infrastructure platform that combines GPU cloud, inference APIs, AI orchestration software, and enterprise AI infrastructure. Our platform powers AI workloads across cloud, hybrid, and on-prem environments using state-of-the-art NVIDIA technologies and open-source AI frameworks. We are looking for a hands-on GPU Infrastructure Engineer with deep expertise in NVIDIA GPU systems, inference platforms, clustering, and high-performance networking. This role requires someone who has built and operated production GPU environments and understands the entire stack from hardware and drivers to inference serving and performance optimization. Role Overview As a GPU Infrastructure Engineer, you will be responsible for deploying, managing, and optimizing NVIDIA GPU infrastructure used for AI training and inference. You will work on GPU servers, cluster orchestration, partitioning technologies, networking, monitoring, and inference frameworks such as NVIDIA Triton Inference Server. You should be comfortable troubleshooting issues at the hardware, OS, networking, and application layers. Responsibilities Deploy, configure, and maintain NVIDIA GPU servers and clusters. Install and manage NVIDIA drivers, CUDA, cu DNN, NCCL, Tensor RT, and related software stacks. Build and oper .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.