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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 the next generation AI infrastructure platform that enables organizations to deploy, scale, and monetize AI workloads across cloud, on-premises, and hybrid environments. Our platform combines GPU cloud infrastructure, inference APIs, model deployment services, RAG pipelines, fine-tuning capabilities, and AI orchestration software into a unified AI stack. We are seeking an experienced and hands-on AI Inference Engineer to design, optimize, and scale large-scale AI inference systems supporting thousands of concurrent users and enterprise AI workloads. Role Overview As an AI Inference Engineer, you will be responsible for deploying, optimizing, and operating open-source and commercial AI models across NVIDIA GPU infrastructure. You will work at the intersection of machine learning, distributed systems, GPU optimization, and cloud infrastructure to deliver low-latency, high-throughput AI services. This is a highly technical role requiring deep expertise in LLM serving, GPU performance tuning, model optimization, inference frameworks, and large-scale production deployments. Responsibilities AI Model Deployment & Serving Deploy and manage Large Language Models (LLMs), multimodal models, vision models, speech models, and embedding models in production. Build and optimize inference .
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.