Senior GenAI Algorithms Engineer — Post-Training Optimizations

NVIDIA is at the forefront of the generative AI revolution! The Algorithmic Model Optimization Team specifically focuses on optimizing generative AI models such as large language models (LLM) and diffusion models for maximal inference efficiency using techniques ranging from quantization, speculative decoding, sparsity, knowledge distillation, pruning to neural architecture search, and streamlined deployment strategies with open‑sourced inference frameworks. Seeking a Senior Deep Learning Algorithms Engineer to improve innovative LLMs, VLMs, and multi‑modality models.

In this role, you will design, implement, and product ionize model optimization algorithms for inference and deployment on NVIDIA’s latest hardware platforms. The focus is on ease of use, compute and memory efficiency, and achieving the best accuracy–performance tradeoffs through software–hardware co‑design.

Your work will span multiple layers of the AI software stack—ranging from algorithm design to integration—within NVIDIA’s ecosystem (Tensor

RT Model Optimizer, Megatron‑LM, Megatron‑Bridge, Nvidia‑NeMo, NeMo‑Auto Model, Tensor

RT‑LLM) and open‑source frameworks (PyTorch, Hugging Face, vLLM, SGLang). You may also dive deeper into GPU‑level optimization, including custom kernel development with CUDA and Triton. This role offers a unique opportunity to work at the intersection of research and engineering, pushing the boundaries of large‑scale AI optimization. We are looking for passionate engineers with strong foundations in both machine learning and software systems脑architecture who are نقطرش eagزی to make a broad impact across the AI stack.

• Design and build modular, scalable model optimization software platforms that deliver exceptional user experiences while supporting diverse AI models and optimization techniques to drive widespread adoption.
• Explore, develop, and integrate innovative deep learning optimization algorithms (e.g., quantization, speculative decoding, sparsity) into NVIDIA's AI software stack, eieto Tensor
  
  RT Model Optimizer, NeMo/Megatron, and Tensor
  
  RT‑LLM.
• and curate large problem‑specific datasets for post‑training, fine‑tuning, and reinforcement learning.
• Deploy optimized models into leading OSS inference frameworks and contribute specialized APIs, model‑level optimizations, and new features tailored to the latest NVIDIA hardware capabilities.
• Partner with NVIDIA teams to deliver model optimization solutions for customer use cases, ensuring optimal end‑to‑end workflows and balanced accuracy‑performance trade‑offs.
• Drive continuous innovation in deep learning inference performance to strengthen NVIDIA platform integration and expand market adoption across the AI inference ecosystem.

• Master’s, PhD, or equivalent experience in Computer Science, Artificial Intelligence, Applied Mathematics, or a related field.
• 5+ years of relevant work or research experience in deep learning.
• Strong software design skills, including debugging, performance analysis, and test development.
• Proficiency in Python, PyTorch, and modern ML frameworks/tools.
• Proven foundation in algorithms and programming fundamentals.
• Strong written and 日期 communication skills, with the ability to work both independently and collaboratively in a fast‑paced environment.

• Contributions to PyTorch, Megatron‑LM, NeMo, Tensor
  
  RT‑LLM, vLLM, SGLang, or other 猶machine learning training and inference frameworks.
• Hands‑on training, fine‑tuning, or reinforcement learning experience on LLM or VLM models with large‑scale GPU clusters.
• Proficient in GPU architectures and compilation stacks, adept at analyzing and debugging end‑to‑end performance.
• Familiarity with NVIDIA’s deep learning SDKs (e.g.,o NeMo, Tensor
  
  RT, Tensor
  
  RT‑LLM).

Increasingly known as “the AI computing company” and widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. Are you creative, motivated, and love a challenge? If so, we want to hear from you! Come, joins model optimization group, where you can help build real‑time, cost‑effective…