Deep Learning Algorithm Engineer - New College Graduate 2025

Details

Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work.

We are looking for a Deep Learning Algorithms Engineer who will focus on optimizing and deploying deep learning models (LLMs and VLMs) for efficient, low-latency, high-throughput inference across diverse GPU platforms. You will collaborate with research scientists, software engineers, and hardware specialists to bring cutting-edge AI models from prototype to production.

Responsibilities

• Optimize deep learning models for low-latency, high-throughput inference.
• Convert and deploy models using frameworks such as TensorRT and TensorRT-LLM.
• Understand, analyze, profile, and optimize performance of deep learning workloads on state-of-the-art hardware and software platforms.
• Collaborate with internal and external researchers to ensure seamless integration of models from training to deployment.

Requirements

• Pursuing or recently completed a Master’s or PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related field (or equivalent experience).
• Experience in deep learning or applied machine learning.
• Strong foundation in deep learning algorithms, including hands-on experience with Large Language Models (LLMs) and Vision-Language Models (VLMs).
• Deep understanding of transformer architectures, attention mechanisms, and inference bottlenecks.
• Proficient in building and deploying models using PyTorch or TensorFlow in production-grade environments.
• Solid programming skills in Python and C++.

Ways to stand out (Preferred / Nice-to-have)

• Proven experience deploying LLMs or VLMs at scale in real-world applications.
• Hands-on experience with model optimization and serving frameworks such as TensorRT, TensorRT-LLM, vLLM, and SGLang.

Team & Context

• The team contributes to datacenter deployments, hardware design, and system software development and collaborates with DL research teams, CUDA Kernel and DL framework development teams, and silicon architecture teams.

Salary and Benefits

• Base salary range: 148,000 USD - 235,750 USD (determined based on location, experience, and pay of employees in similar positions).
• Eligible for equity and benefits.

Other details

• Location: Santa Clara, CA, United States.
• Employment type: Full time.
• Applications accepted at least until October 3, 2025.

NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer.