NVIDIA

4 weeks ago

Senior Solutions Architect, Generative AI Research

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Senior Solutions Architect for NVIDIA’s Higher Education and Research Team, partnering with universities to shape cutting-edge work on foundation models, generative AI, multimodal AI, and AI agents. Advises labs on GPU-accelerated training, inference studies, tool-use methods, data pipelines, and scalable workflows; helps build prototypes and translates lab feedback into actionable guidance for NVIDIA teams.

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Manager level

Key Responsibilities

•Partner with universities to shape high-impact work on foundation models, generative AI, multimodal AI, reasoning systems, AI agents, and AI systems.
•Advise labs on GPU-accelerated training, inference studies, agent evaluation, tool-use methods, data pipelines, scaling experiments, and reproducible workflows.
•Help build research prototypes with researchers utilizing the NVIDIA full stack.
•Analyze throughput, memory, parallelism, latency, and scaling across workstations, multi-GPU servers, and campus HPC clusters.
•Translate lab feedback into technical examples, workshops, roadmap input, and adoption guidance for NVIDIA teams.

Travel: Medium travel

Pay and Benefits

Salary: USD 184,000 - 287,500 annually

Perks:EquityBenefits

Key Requirements

•BS, MS or PhD in Computer Science, AI/ML, Electrical Engineering, Applied Mathematics, or a related technical field, or equivalent experience.
•8+ years of hands-on experience with AI systems, accelerated computing, distributed training, inference studies, or research-scale generative AI workflows.
•Deep foundational AI expertise across LLMs, VLMs, multimodal models, reasoning, long-context models, fine-tuning, post-training, agentic AI, and evaluation.
•Strong systems fluency in PyTorch or JAX, Python, Linux, distributed AI, data loading, checkpointing, memory optimization, batching, scheduling, latency, and throughput.
•Experience guiding faculty, graduate researchers, and research-computing teams on benchmarks, reproducibility, reliability, safety, agent evaluation, and research impact.
•Clear communication, technical judgment, and comfort turning complex model, agent, and infrastructure questions into practical next steps for labs.

Experience:8+ yearsAIResearchHPCAccelerated computing

Skills:CommunicationPresentationCollaborationProblem-solvingStakeholder management

Tech Stack:PyTorchJAXPythonLinuxDistributed AIData loadingCheckpointingMemory optimizationNVIDIA NeMoMegatronTensorRT-LLMTritonRAPIDS

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

4 weeks ago

Senior Solutions Architect, Generative AI Research

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Manager level

Key Responsibilities

•Partner with universities to shape high-impact work on foundation models, generative AI, multimodal AI, reasoning systems, AI agents, and AI systems.
•Advise labs on GPU-accelerated training, inference studies, agent evaluation, tool-use methods, data pipelines, scaling experiments, and reproducible workflows.
•Help build research prototypes with researchers utilizing the NVIDIA full stack.
•Analyze throughput, memory, parallelism, latency, and scaling across workstations, multi-GPU servers, and campus HPC clusters.
•Translate lab feedback into technical examples, workshops, roadmap input, and adoption guidance for NVIDIA teams.

Travel: Medium travel

Pay and Benefits

Salary: USD 184,000 - 287,500 annually

Perks:EquityBenefits

Key Requirements

•BS, MS or PhD in Computer Science, AI/ML, Electrical Engineering, Applied Mathematics, or a related technical field, or equivalent experience.
•8+ years of hands-on experience with AI systems, accelerated computing, distributed training, inference studies, or research-scale generative AI workflows.
•Deep foundational AI expertise across LLMs, VLMs, multimodal models, reasoning, long-context models, fine-tuning, post-training, agentic AI, and evaluation.
•Strong systems fluency in PyTorch or JAX, Python, Linux, distributed AI, data loading, checkpointing, memory optimization, batching, scheduling, latency, and throughput.
•Experience guiding faculty, graduate researchers, and research-computing teams on benchmarks, reproducibility, reliability, safety, agent evaluation, and research impact.
•Clear communication, technical judgment, and comfort turning complex model, agent, and infrastructure questions into practical next steps for labs.

Experience:8+ yearsAIResearchHPCAccelerated computing

Skills:CommunicationPresentationCollaborationProblem-solvingStakeholder management

Tech Stack:PyTorchJAXPythonLinuxDistributed AIData loadingCheckpointingMemory optimizationNVIDIA NeMoMegatronTensorRT-LLMTritonRAPIDS

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