NVIDIA Hiring in Bengaluru for College Graduate (Tech) 2026 batch. Explore AI inference optimization roles with competitive packages. Join NVIDIA’s cutting-edge GPU technology team in Bangalore, India.

NVIDIA Hiring in Bengaluru, India has announced exciting opportunities for College Graduate (Tech) 2026 batch students. The global leader in accelerated computing and artificial intelligence is seeking talented engineers to join their inference optimization team in Bangalore. This NVIDIA Hiring initiative focuses on recruiting fresh graduates who will work on cutting-edge Large Language Models (LLMs), distributed computing, and GPU optimization technologies that power the future of AI infrastructure.

About NVIDIA’s Bengaluru Operations

Bengaluru, India, serves as one of NVIDIA’s critical engineering hubs, contributing to groundbreaking innovations in GPU architecture, AI frameworks, and deep learning infrastructure. The city’s thriving tech ecosystem makes it an ideal location for graduates beginning their careers in advanced computing. NVIDIA in Bangalore houses teams working on TensorRT, CUDA, and various AI inference frameworks that define industry standards.

Role Overview: College Graduate (Tech) Position Details

Company: NVIDIA Corporation
Position: College Graduate (Tech) – Inference Optimization Engineer
Batch: 2026
Location: Bengaluru, Karnataka, India
Employment Type: Full-time

This role represents a unique opportunity for 2026 graduates to work at the intersection of artificial intelligence, systems engineering, and high-performance computing.

Key Responsibilities for NVIDIA College Graduates

1. Industry Benchmark Optimization

• Own end-to-end optimization pipelines for AI inference workloads
• Implement advanced quantization and scheduling algorithms
• Optimize memory management across TensorRT-LLM, SGLang, and vLLM frameworks
• Drive distributed inference performance improvements

2. Next-Generation AI Workload Development

• Define cutting-edge inference benchmarks for emerging AI applications
• Shape multi-turn coding assistants and agentic workflow systems
• Collaborate with framework development and CUDA kernel teams
• Push performance boundaries on large-scale LLM-MoE models, vision-language models, and video diffusion systems

3. Distributed System Architecture

• Design scalable execution strategies from single-GPU to rack-scale clusters
• Manage performance optimization across multi-GPU configurations
• Implement efficient communication protocols for distributed inference

4. Performance Analysis & Methodology

• Apply roofline analysis for systematic performance profiling
• Decompose bottlenecks across CUDA kernels, frameworks, and serving layers
• Establish best practices for inference optimization

5. Open-Source Ecosystem Contributions

• Contribute to TensorRT-LLM, vLLM, SGLang, and related projects
• Partner with architecture, compiler, and kernel teams
• Influence GPU roadmap development based on real-world workload data

6. Technical Leadership Opportunities

• Drive cross-functional execution on critical benchmark timelines
• Collaborate with world-class engineering teams
• Raise technical standards through innovation and best practices

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Required Qualifications for NVIDIA Hiring 2026

Educational Background:

• Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or equivalent technical field
• 2026 graduation batch from recognized institutions

Technical Skills:

• Minimum 2 years of relevant software development experience (including internships, research projects, or co-op programs)
• Strong proficiency in Python or C++ programming
• Solid understanding of software design patterns and engineering principles
• Hands-on expertise with deep learning frameworks (PyTorch or JAX)
• Proven track record in delivering performance improvements in deep learning inference or high-performance computing systems

Specialized Knowledge:

• Deep understanding of LLM/VLM architectures and inference mechanisms
• Knowledge of attention mechanisms, KV caching, and batching strategies
• Familiarity with decode-phase bottlenecks and speculative decoding techniques
• Understanding of disaggregated serving architectures

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Preferred Qualifications That Make You Stand Out

Advanced Framework Experience:

• Prior work with LLM frameworks like TensorRT-LLM, vLLM, or SGLang
• Experience with deep learning compilers for inference optimization
• Implementation experience with deployment algorithms

Performance Optimization Expertise:

• Performance modeling and profiling skills
• Debug and code optimization experience with DL/HPC applications
• Systematic approach to performance bottleneck resolution

Distributed Systems Knowledge:

• Scale-out inference orchestration using MPI, NCCL, or Kubernetes
• Experience managing large GPU cluster deployments
• Understanding of distributed communication protocols

Low-Level Programming Skills:

• Kernel development expertise (CUTLASS, cuteDSL, tilelang, OpenAI Triton)
• Compiler and runtime path knowledge (torch.compile, graph lowering, operator fusion)
• GPU programming experience with CUDA
• Architectural knowledge of CPUs, GPUs, FPGAs, or specialized AI accelerators

Leadership Experience:

• Track record of leading complex technical programs
• Cross-team collaboration under tight deadlines
• Managing ambiguous, high-impact initiatives

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Why Join NVIDIA in Bengaluru?

1. Cutting-Edge Technology Exposure Work on technologies that power ChatGPT, Midjourney, and other revolutionary AI applications. NVIDIA’s GPUs and software frameworks are the foundation of modern AI infrastructure.

2. Learning and Growth Opportunities Access to world-class mentorship, continuous learning programs, and exposure to bleeding-edge research in AI, GPU computing, and distributed systems.

3. Competitive Compensation Industry-leading salary packages, stock options, performance bonuses, and comprehensive benefits for college graduates.

4. Innovation-Driven Culture Join a company that encourages experimentation, values technical excellence, and rewards innovative problem-solving.

5. Global Impact Your work will directly influence AI applications used by millions worldwide, from autonomous vehicles to healthcare diagnostics.

How to Apply for NVIDIA Hiring 2026

Interested candidates from the 2026 batch should:

1. Visit NVIDIA’s official careers portal
2. Search for “College Graduate (Tech)” positions in Bengaluru
3. Prepare your resume highlighting relevant projects, internships, and technical skills
4. Showcase any contributions to open-source projects or research publications
5. Include links to GitHub repositories, technical blogs, or portfolio work
6. Submit your application through the official channel

Application Tips for Success

• Highlight Relevant Projects: Emphasize any work related to deep learning, performance optimization, or distributed systems
• Demonstrate Problem-Solving: Include specific examples of technical challenges you’ve overcome
• Showcase Learning Agility: Highlight your ability to quickly master new technologies and frameworks
• Quantify Achievements: Use metrics to demonstrate performance improvements or impact
• Prepare for Technical Interviews: Review fundamental computer science concepts, system design, and coding problems

Frequently Asked Questions (FAQs)

1. Is this NVIDIA Hiring opportunity only for 2026 graduates?

Yes, this specific role targets students graduating in 2026 with degrees in Computer Science, Computer Engineering, Electrical Engineering, or related technical fields. The position is designed for fresh talent entering the workforce.

2. What is the typical selection process for NVIDIA College Graduate positions in Bengaluru?

The selection process typically includes: online application screening, coding assessments, technical interviews (covering data structures, algorithms, system design), and behavioral interviews. Some positions may also include take-home assignments or project presentations.

3. Does NVIDIA provide relocation assistance for candidates joining the Bengaluru office?

NVIDIA typically offers relocation assistance packages for selected candidates, including moving allowances, temporary accommodation, and settling-in support. Specific details are discussed during the offer stage.