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NVIDIA

Senior Deep Learning Algorithms Engineer

Posted 3 Days Ago
Be an Early Applicant
Remote
2 Locations
300K-400K
Senior level
Remote
2 Locations
300K-400K
Senior level
Optimize and deploy deep learning models for fast inference. Collaborate with teams to transition AI models from prototype to production.
The summary above was generated by AI

We are now looking for a Senior DL Algorithms Engineer! We are seeking a highly skilled Deep Learning Algorithms Engineer with hands-on experience optimizing and deploying Large Language Models (LLMs) and Vision-Language Models (VLMs) in production environments.  In this role, you will focus on optimizing and deploying deep learning models for efficient and fast 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.
 

What you will be doing:

  • 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.

What we want to see:

  • Master’s or PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related field (or equivalent experience)

  • 5+ years of professional experience in deep learning or applied machine learning.

  • Strong foundation in deep learning algorithms, including hands-on experience with LLMs and 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 from the crowd:

  • 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, SGLang.

Top Skills

C++
Python
PyTorch
TensorFlow
Tensorrt

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