Nvidia
Technology
SeniorSoftwareEngineer,GenerativeAI
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Software Engineer, Generative AI at Nvidia. Skills: Generative AI, Physical AI, ML infrastructure, Distributed systems. Design scalable infrastructure. Build scalable infrastructure”
What You'll Achieve.
Accelerate experiments; Accelerate deployments; Move research faster; Move production faster; Move research efficiently; Move production efficiently
Industry & Context.
Root cause analysis; Troubleshooting
What They're Looking For.
Must Have
Masters Degree in CS or related, 6 years relevant work experience, Proficiency in Python, Proficiency in C++/Go/Rust, Experience with orchestration systems, Experience with scheduling systems, Experience with scalable storage, Experience with data pipelines, Ability to work across teams, Ability to drive technical clarity, Ability to deliver robust solutions
Nice to Have
Experience building model training infrastructure, Experience optimizing model training infrastructure, Hands-on distributed compute environments, Hands-on high-performance systems, Familiarity with synthetic data, Familiarity with simulation pipelines, Familiarity with large multimodal datasets, Contributions to open-source infrastructure, Contributions to large-scale internal tooling
What You'll Do.
Design scalable infrastructure
Build scalable infrastructure
Operate scalable infrastructure
Support large-scale data pipelines
Develop high-throughput systems
Orchestrate workflows
Collaborate across teams
Accelerate experiments
Accelerate deployments
Improve system reliability
Improve system performance
Improve system observability
Contribute to infrastructure strategy
Improve compute efficiency
How You'll Work.
Team & Collaboration
Across research teams; Across optimization teams; Across platform teams
Full Job Description
We are now looking for a Senior Software Engineer for Generative AI Research! At NVIDIA, we believe the next generation of AI will be physical AI – systems that perceive, reason, and act in the real world. Building these models requires building robust systems that span across large-scale compute, multimodal datasets, simulation-driven synthetic data, and real-time reasoning for robots and autonomous systems. Our Cosmos infrastructure team sits at the heart of this mission. We build the systems that make it possible to train Cosmos, NVIDIA’s world foundation model for physical AI. Cosmos enables large-scale AI models for robots, autonomous agents, and AI systems to understand, plan, and act in complex environments. Our team develops the Cosmos platform infrastructure that powers model training, data pipelines, simulation, and deployment at scale, enabling research and production to move faster and more efficiently than ever before. This role is a unique opportunity to work on infrastructure that directly enables physical AI at scale – from optimizing massive data pipelines to designing training workflows that support foundation models, and from scaling distributed compute systems to building the backbone for simulation-driven experimentation. ****What You’ll Be Doing:**** * Design, build, and operate scalable infrastructure for training Cosmos and supporting large-scale data pipelines * Develop high-throughput systems for data processing, retrieval, and workflow orchestration * Collaborate across research, optimization, and platform teams to accelerate experiments and deployments * Improve system reliability, performance, and observability across distributed compute environments * Contribute to long-term infrastructure strategy for training, data management, and large-scale compute efficiency ****What We Need to See:**** * A Masters Degree in Computer Science, Computer Engineering, related STEM Degree, or equivalent experience. * Strong engineering background in dis
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