NVIDIA

3 months ago

Senior Software Engineer, AI Networking

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 15 hours agoStatus: Live

Job Summary

Senior software engineer on the AI Networking co-design and benchmark R&D team focused on building and productizing ML-based tools to optimize AI workloads at datacenter scale. Work spans distributed deep learning, LL M training/inference stacks, and collaboration across hardware, software, and networking libraries to deliver performance analytics and optimization for large GPU/CPU clusters.

Location: Santa Clara, Seattle

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Design and implement resource allocation and combinatorial optimization techniques (e.g., reinforcement learning, LLM agents for DSE, Bayesian optimization and other multi-objective optimization techniques) to optimize LLM models at datacenter scale.
•Research, develop, and deploy AI/ML techniques to optimize large-scale Deep Learning (LLM) training and inference on NVIDIA supercomputers and distributed systems, focusing on high-performance networking and NVIDIA communication libraries.
•Build and productionize ML-based tools for performance prediction and optimization, with emphasis on networking aspects.
•Develop and deploy a scalable data curation pipeline capable of handling complex data types (e.g., time series and PyTorch model graphs) to support training of high-performance ML models.
•Collaborate across hardware and software teams to deliver performance analysis insights and drive optimization efforts.

Key Requirements

•PhD or Master’s degree in Computer Science, Software Engineering, or equivalent experience
•4+ years of experience applying machine learning techniques to computer architecture and system optimization problems, with intersection of HPC, networking, and AI applications
•Hands-on experience developing and deploying learning algorithms (e.g., reinforcement learning, offline RL, supervised learning) for optimization in computer architecture, system design, or networking
•Proficiency in building and using ML models with PyTorch, TensorFlow, or JAX
•Strong programming capabilities in Python, Bash, and C++

Experience:4+ yearsAIHPCNetworkingData centersLLMDeep Learning

Education:Master's

Skills:CommunicationCollaborationTeamworkProblem-solving

Tech Stack:PythonBashC++PyTorchTensorFlowJAXCUDANCCLRoCERDMAKinetoGNNsReinforcement learningBayesian optimization

Company Brief

NVIDIA

Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor

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NVIDIA

3 months ago

Senior Software Engineer, AI Networking

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 15 hours agoStatus: Live

Job Summary

Location: Santa Clara, Seattle

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Design and implement resource allocation and combinatorial optimization techniques (e.g., reinforcement learning, LLM agents for DSE, Bayesian optimization and other multi-objective optimization techniques) to optimize LLM models at datacenter scale.
•Research, develop, and deploy AI/ML techniques to optimize large-scale Deep Learning (LLM) training and inference on NVIDIA supercomputers and distributed systems, focusing on high-performance networking and NVIDIA communication libraries.
•Build and productionize ML-based tools for performance prediction and optimization, with emphasis on networking aspects.
•Develop and deploy a scalable data curation pipeline capable of handling complex data types (e.g., time series and PyTorch model graphs) to support training of high-performance ML models.
•Collaborate across hardware and software teams to deliver performance analysis insights and drive optimization efforts.

Key Requirements

•PhD or Master’s degree in Computer Science, Software Engineering, or equivalent experience
•4+ years of experience applying machine learning techniques to computer architecture and system optimization problems, with intersection of HPC, networking, and AI applications
•Hands-on experience developing and deploying learning algorithms (e.g., reinforcement learning, offline RL, supervised learning) for optimization in computer architecture, system design, or networking
•Proficiency in building and using ML models with PyTorch, TensorFlow, or JAX
•Strong programming capabilities in Python, Bash, and C++

Experience:4+ yearsAIHPCNetworkingData centersLLMDeep Learning

Education:Master's

Skills:CommunicationCollaborationTeamworkProblem-solving

Tech Stack:PythonBashC++PyTorchTensorFlowJAXCUDANCCLRoCERDMAKinetoGNNsReinforcement learningBayesian optimization

Company Brief

NVIDIA

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor