Principal Artificial Intelligence Algorithms Engineer
at Nvidia
π Santa Clara, United States
USD 272,000-425,500 per year
SCRAPED
Used Tools & Technologies
Not specified
Required Skills & Competences ?
Python @ 6 GitHub @ 4 Algorithms @ 4 Machine Learning @ 4 Hiring @ 4 Debugging @ 6 API @ 4 LLM @ 4 PyTorch @ 4 GPU @ 4Details
NVIDIA is hiring for the core AI Frameworks team (Megatron Core and NeMo Framework) to design, develop, and optimize real-world workloads for large language models (LLMs) and multimodal foundation models. The role focuses on expanding the capabilities of open-source, scalable, cloud-native frameworks to support the full model lifecycle: pretraining, reasoning, alignment, customization, evaluation, deployment, and tooling to optimize performance and user experience. Work spans algorithm design, distributed training, model parallel paradigms, performance tuning, and building robust APIs and toolkits.
Responsibilities
- Design and implement distributed training algorithms and model parallel paradigms for large-scale AI training and inference.
- Develop algorithms for AI/Deep Learning (DL), data analytics, machine learning, or scientific computing.
- Contribute to and advance open-source projects: Megatron Core (https://github.com/NVIDIA/Megatron-LM/tree/main/megatron/core) and NeMo Framework (https://github.com/nvidia-nemo).
- Solve end-to-end AI training and inference challenges across data orchestration, preprocessing, training, tuning, and deployment.
- Work across the software stack at the intersection of computer architecture, libraries, frameworks, and AI applications.
- Implement performance tuning and optimizations, including mixed precision recipes on next-gen NVIDIA GPU architectures.
- Research, prototype, and develop robust and scalable AI tools and pipelines; define APIs and expand toolkits and libraries.
Requirements
- MS, PhD or equivalent experience in Computer Science, AI, Applied Math, or related fields and 10+ years of industry experience.
- Experience with AI frameworks such as PyTorch or JAX and/or inference/deployment environments (examples: TRTLLM, vLLM, SGLang).
- Proficient in Python programming, software design, debugging, performance analysis, test design, and documentation.
- Strong understanding of AI/Deep-Learning fundamentals and practical applications.
- Demonstrated ability to work across multiple engineering initiatives and to improve AI libraries with new innovations.
Preferred / Ways to Stand Out
- Hands-on experience in large-scale AI training with a deep understanding of compute system concepts (latency/throughput bottlenecks, pipelining, multiprocessing) and demonstrated performance analysis/tuning expertise.
- Expertise in distributed computing, model parallelism, and mixed precision training.
- Prior experience with generative AI techniques applied to LLM and multimodal learning (text, image, video).
- Knowledge of GPU/CPU architecture, numerical software, and contributions to open-source deep learning frameworks.
Benefits
- Base salary range: 272,000 USD - 425,500 USD (final base depends on location, experience, and comparable roles).
- Eligible for equity and other benefits (see NVIDIA benefits page: https://www.nvidia.com/en-us/benefits/).
- NVIDIA emphasizes a diverse and inclusive work environment and is an equal opportunity employer.
Other Details
- Location: Santa Clara, CA, United States.
- Time type: Full time.
- Applications accepted at least until August 15, 2025.