GenAI Systems Engineer: Scale Training & Inference (Equity)

NVIDIA Corporation; New York (NY); On-site; USD 152,000 - 288,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA Corporation is seeking a Senior GenAI Algorithms Engineer to drive foundation model development, training, and deployment, spanning data prep, training, post-training, and inference optimization. You will contribute to Megatron-LM, Megatron Bridge, and NeMo-RL.

Collaborating with research, product, and infrastructure teams, you will design new algorithms and optimize systems for scalable, efficient AI workflows across cloud and edge platforms.

Qualifications

• MS or PhD in Computer Science, AI, Applied Mathematics, or a related field.
• 5+ years of relevant industry experience.
• Strong foundation in machine learning, deep learning, and optimization.
• Excellent software engineering skills, including Python and PyTorch.
• Experience building high-performance software for large-scale AI systems.
• Strong analytical, debugging, and performance optimization skills.
• Excellent communication and collaboration skills.

Responsibilities

• Data Curation & Readiness: Design scalable systems for preparing high-quality multimodal datasets for frontier foundation model training.
• Training Efficiency: Develop algorithms and systems that improve the scalability, efficiency, and cost of large-scale pre-training and post-training.
• Inference Efficiency: Advance techniques that improve inference performance, reduce deployment cost, and enable efficient serving across cloud and edge platforms.
• Open-Source AI Infrastructure: Develop reusable infrastructure and contribute brand new model support to NVIDIA's open-source GenAI training platform.

Skills

Machine learning

Deep learning

Optimization

Python

PyTorch

Systems design

Education

MS/PhD in CS/AI/Applied Math

Tools

Megatron-LM

Megatron Bridge

NeMo-RL

Hugging Face Transformers

Job description

NVIDIA Corporation is seeking a Senior GenAI Algorithms Engineer to drive foundation model development, training, and deployment, spanning data prep, training, post-training, and inference optimization. You will contribute to Megatron-LM, Megatron Bridge, and NeMo-RL.

Collaborating with research, product, and infrastructure teams, you will design new algorithms and optimize systems for scalable, efficient AI workflows across cloud and edge platforms.