Deep Learning Engineer (New Grad)

About This Role

NVIDIA is hiring Deep Learning Engineers from campus to work on AI frameworks, GPU-accelerated training libraries, and inference toolkits used by researchers and developers worldwide. You will be close to the hardware — optimizing neural networks to run faster on the world's most powerful AI accelerators.

Job Overview

• Job Title: Deep Learning Engineer (New Grad)
• Company: NVIDIA
• Location: Santa Clara, CA / Austin, TX / Seattle, WA / Durham, NC / New York, NY
• Job Type: Full-time
• Experience Level: Entry-level (0–2 years)
• Salary Range: $40–$56/hr
• Posted Date: 2026-06-01
• Application Deadline: 2026-07-01

Role Context

NVIDIA's DL engineering teams sit between hardware and software — building the tools that let the rest of the AI world train and deploy models. You might work on TensorRT, cuDNN, NeMo, or CUDA-accelerated kernels depending on your team. New grad engineers ramp up through hands-on projects with senior engineers who have written foundational deep learning software.

Key Responsibilities

• Develop and optimize deep learning model components in Python and CUDA C++
• Benchmark model and kernel performance on NVIDIA GPU architectures
• Implement quantization, pruning, and distillation techniques for inference efficiency
• Contribute to NVIDIA's open-source AI framework libraries (NeMo, TensorRT, cuDNN)
• Write reproducible test cases and performance regression benchmarks
• Collaborate with hardware architects to exploit new GPU features in software

Requirements & Skills

• Bachelor's or Master's in CS, Electrical Engineering, or a related technical discipline (2024–2025)
• Strong Python skills and familiarity with PyTorch or TensorFlow
• Interest in GPU computing, CUDA, or hardware-aware ML optimization
• Solid understanding of deep learning architectures (CNNs, transformers, diffusion models)
• C or C++ programming experience is a significant advantage
• Exposure to profiling tools (Nsight, nvtop, or similar) is a bonus

Benefits & Work Conditions

• $40–$56/hr with NVIDIA RSUs and annual bonus
• Hybrid schedule with flexible remote policy
• Access to cutting-edge GPU hardware for personal research and learning
• Comprehensive health, dental, and vision benefits from day one
• Conference and publication support for technically active engineers

Who Should Apply

New grads who want to work at the intersection of AI software and GPU hardware. If you find low-level performance optimization satisfying and want your work to power the entire AI industry's training runs, NVIDIA is a uniquely influential place to start your career.

About the Company

NVIDIA designs GPUs and accelerated computing platforms that underpin the majority of AI training workloads globally. Its software ecosystem — CUDA, TensorRT, NeMo, and Triton — is foundational to the modern AI stack across research, industry, and cloud providers.

How to Apply

Apply on NVIDIA's careers site. Search "Deep Learning Engineer New Grad." The interview process includes coding challenges, a technical discussion on deep learning, and a project or paper review for candidates with relevant research experience.