Senior AI Systems and Algorithms Engineer

Jobtailor; California (MO); On-site; USD 180,000 - 260,000; Full time

Job summary

NVIDIA is seeking a highly skilled researcher/engineer to advance foundation models, train and deploy multimodal data pipelines, and optimize large-scale AI systems. The role emphasizes building scalable infrastructure, reducing costs, and enabling efficient inference across cloud and edge environments, with extensive work on Megatron-LM, Megatron Bridge, and NeMo-RL.

Ideal candidates have 5+ years of experience, strong ML/DL foundations, and hands-on PyTorch development in distributed training

Qualifications

• MS or PhD in Computer Science or related field (or equivalent experience).
• 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.
• Experience with distributed training at scale, such as Megatron-LM, Megatron Bridge, FSDP, and TP/PP/CP/DP.
• Experience with optimizer research and efficient sparse or long-context attention.
• Experience with supervised fine-tuning, reinforcement learning for LLMs, PPO, GRPO, asynchronous RL, or NeMo-RL.
• Experience with model compression, quantization, pruning, knowledge distillation, neural architecture search, or diffusion/non-autoregressive language models.
• Experience contributing to open-source AI frameworks such as Megatron-LM, Megatron Bridge, NeMo-RL, or Hugging Face Transformers
• Experience with GPU performance optimization, distributed systems, latency/throughput analysis, and profiling of large-scale AI workloads

Responsibilities

• Advance the state of the art in foundation model development, training, and deployment.
• Design scalable systems for preparing high-quality multimodal datasets for frontier foundation model training.
• Develop algorithms and systems that improve scalability, efficiency, and cost of large-scale pre-training and post-training.
• Advance techniques that improve inference performance, reduce deployment cost, and enable efficient serving across cloud and edge platforms.
• Develop reusable infrastructure and contribute new model support to NVIDIA's open-source GenAI training platform.
• Collaborate with research, product, and infrastructure teams to design new algorithms and optimize existing systems.
• Contribute to NVIDIA's open-source AI stack, including Megatron-LM, Megatron Bridge, and NeMo-RL

Skills

Foundation Model Development

Machine Learning

Deep Learning

Python Programming

PyTorch Framework

Education

MS or PhD in Computer Science or related field

Tools

Megatron-LM

Megatron Bridge

NeMo-RL

Hugging Face Transformers

Job description

• Advance the state of the art in foundation model development, training, and deployment
• Design scalable systems for preparing high-quality multimodal datasets for frontier foundation model training
• Develop algorithms and systems that improve the scalability, efficiency, and cost of large-scale pre-training and post-training
• Advance techniques that improve inference performance, reduce deployment cost, and enable efficient serving across cloud and edge platforms
• Develop reusable infrastructure and contribute new model support to NVIDIA's open-source GenAI training platform
• Collaborate with research, product, and infrastructure teams to design new algorithms and optimize existing systems
• Contribute to NVIDIA's open-source AI stack, including Megatron-LM, Megatron Bridge, and NeMo-RL

Requirements

• MS or Ph.D in Computer Science, AI, Applied Mathematics, or a related field (or equivalent experience)
• 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
• Experience with distributed training at scale, such as Megatron-LM, Megatron Bridge, FSDP, and TP/PP/CP/DP
• Experience with optimizer research and efficient sparse or long-context attention
• Experience with supervised fine-tuning, reinforcement learning for LLMs, PPO, GRPO, asynchronous RL, or NeMo-RL
• Experience with model compression, quantization, pruning, knowledge distillation, neural architecture search, or diffusion/non-autoregressive language models
• Experience contributing to open-source AI frameworks such as Megatron-LM, Megatron Bridge, NeMo-RL, or Hugging Face Transformers
• Experience with GPU performance optimization, distributed systems, latency/throughput analysis, and profiling of large-scale AI workloads

Core Competencies

Demonstrates expertise in foundation model development, including machine learning and deep learning, with a strong focus on optimizing large-scale AI systems. Proficient in Python and PyTorch, with experience in distributed training and contributing to open-source AI frameworks.

Highest-signal resume keywords

• Foundation Model Development
• Machine Learning
• Deep Learning
• Python Programming
• PyTorch Framework

ATS Optimization Keywords

Hard Skills

• Machine Learning
• Deep Learning
• Optimization
• Distributed Training
• Model Compression
• Quantization
• Pruning
• Neural Architecture Search
• Reinforcement Learning
• Performance Optimization

Soft Skills

• Analytical Skills
• Debugging Skills

Certifications & Qualifications

• MS or Ph.D in Computer Science
• AI
• Applied Mathematics

Industry Keywords

• AI Systems