NVIDIA

3 days ago

Distinguished AI Researcher, Advanced Development Engineer

✓ 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

Drive technical vision and co-design for NVIDIA’s AI infrastructure software stack, spanning GPU computing, RDMA networking, NVLink interconnects, storage, and large-scale distributed systems. Lead deep investigations and proof-of-concepts for distributed AI and large-scale systems design, analyze performance and bottlenecks across compute/networking/memory/storage, and guide production environments for massive AI training and inference. Collaborate cross-stack with multiple NVIDIA teams to influence platform direction.

Location: Israel

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Seniority: CXO level

Key Responsibilities

•Research, define, and drive co-design solutions across AI software stacks involving GPU computing, RDMA networking, NVLink interconnects, storage, and distributed infrastructure.
•Lead deep technical investigations and proof-of-concept development for distributed AI, deep learning systems, high-performance computing, virtualization, memory management, and large-scale systems design.
•Collaborate with multiple NVIDIA teams to advance next-generation AI infrastructure technologies and influence cross-stack co-design decisions.
•Analyze end-to-end system bottlenecks and opportunities across compute, networking, memory, and storage to improve performance, scalability, and efficiency.
•Guide the design of production environments supporting massive-scale AI training and inference workloads.

Key Requirements

•M.S. or Ph.D. in Computer Science, Electrical Engineering, Computer Engineering, or equivalent experience.
•20+ years of industry experience in systems design, distributed systems, system software, or related fields.
•Deep background in distributed systems, parallel computation, networking, storage, virtualization, and memory management.
•Experience building, scaling, and supporting environments for massive AI workloads.
•Strong understanding of large-scale systems operational aspects including performance, reliability, scalability, and supportability.

Experience:AI infrastructureDistributed systemsHigh-performance computingHPCDeep learning systems

Education:PhD / Doctorate

Skills:CommunicationCollaborationTechnical leadership

Tech Stack:GPU computingRDMANVLinkStorageVirtualizationMemory managementDistributed infrastructureDeep learningHigh-performance computing

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 days ago

Distinguished AI Researcher, Advanced Development Engineer

✓ 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: Israel

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Seniority: CXO level

Key Responsibilities

•Research, define, and drive co-design solutions across AI software stacks involving GPU computing, RDMA networking, NVLink interconnects, storage, and distributed infrastructure.
•Lead deep technical investigations and proof-of-concept development for distributed AI, deep learning systems, high-performance computing, virtualization, memory management, and large-scale systems design.
•Collaborate with multiple NVIDIA teams to advance next-generation AI infrastructure technologies and influence cross-stack co-design decisions.
•Analyze end-to-end system bottlenecks and opportunities across compute, networking, memory, and storage to improve performance, scalability, and efficiency.
•Guide the design of production environments supporting massive-scale AI training and inference workloads.

Key Requirements

•M.S. or Ph.D. in Computer Science, Electrical Engineering, Computer Engineering, or equivalent experience.
•20+ years of industry experience in systems design, distributed systems, system software, or related fields.
•Deep background in distributed systems, parallel computation, networking, storage, virtualization, and memory management.
•Experience building, scaling, and supporting environments for massive AI workloads.
•Strong understanding of large-scale systems operational aspects including performance, reliability, scalability, and supportability.

Experience:AI infrastructureDistributed systemsHigh-performance computingHPCDeep learning systems

Education:PhD / Doctorate

Skills:CommunicationCollaborationTechnical leadership

Tech Stack:GPU computingRDMANVLinkStorageVirtualizationMemory managementDistributed infrastructureDeep learningHigh-performance computing

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