AI Intern

Nava · Bangalore · Fresher

🚀 Nava – Summer Internship 2026 AI Infrastructure: GPUaaS & Inference Systems 📌 Overview We are hiring highly motivated interns to work on next-generation AI infrastructure, focusing on GPU-as-a-Service (GPUaaS) and large-scale inference systems. This is a systems-heavy role where you will design, build, and optimize infrastructure that powers real-world AI applications at scale. 📍 Location Bangalore (In-person) ⏳ Duration 2 – 6 Months 💰 Stipend ₹60,000 – ₹80,000 per month 🎓 Eligibility B.Tech / M.Tech / MS students Branches: CS / IT / ECE / EE or related Batch: 2026, 2027, 2028 🔥 PPO Opportunity Top-performing interns will be offered a Pre-Placement Offer (PPO). 🛠️ What You’ll Work On Build and scale GPU infrastructure (GPUaaS) for AI workloads Design distributed systems for high availability and performance Develop and optimize model serving & inference pipelines Work on Kubernetes-based orchestration for scalable deployments Improve system performance, monitoring, and resource utilization Handle real-world challenges in latency, throughput, and scaling 💻 Tech Stack / Tools Languages: Python, C++, Go (any one or more) Infrastructure: Kubernetes, Docker AI/ML Serving: Triton Inference Server, PyTorch Systems: Linux, Networking basics Tools: Redis, Prometheus, gRPC (good to have) ✅ Requirements Strong understanding of Data Structures & Algorithms Good grasp of Operating Systems & Computer Networks Interest in systems engineering, backend, or infrastructure Familiarity with Linux & command line tools Basic knowledge of containers / Docker / Kubernetes (preferred) Ability to learn fast and build at scale 🌟 Preferred Qualifications (Nice to Have) Experience with distributed systems or backend projects Contributions to open-source projects Prior exposure to ML systems / model deployment Understanding of GPU computing (CUDA basics is a plus) 🎯 Who Should Apply? Students passionate about systems + AI infrastructure Builders who enjoy solving real-world scalability problems Candidates aiming for high-impact engineering roles

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