Nvidia Ai

60 Nvidia Ai Jobs Hiring Near You

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than ... Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era ...

WI · On-site

$170 - $210/hr

NVIDIA's AI platforms have already made a major impact on the field and are broadly used across leading academic institutions, start‑ups, and industry, including the world's largest enterprise ...

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AI Factory CPU focused Solutions Architect

$64.50 - $85/hr

For this particular role, that means having a deep technical understanding of NVIDIA Reference ... As the technical leader for the CPU components within the NVIDIA AI Factory, you will play an ...

We work at the intersection of partner engineering, NVIDIA's AI platform, and product development. You will lead sophisticated technical projects from initial exploration through architecture ...

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Nvidia Ai Jobs Information

Infographic showing various job openings at Nvidia Ai in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Physical job distribution.

Senior Solutions Architect, GenAI Agentic Networks - Telco

NVIDIA

Remote

Full-time

Re-posted 8 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 245 rated software companies


Job description

Job Summary:
NVIDIA is building AI systems to transform telecommunications networks, and they are seeking a Senior Solutions Architect for their Telco AI team. The role involves designing and deploying Agentic AI applications that automate carrier operations, while providing technical guidance to partners and customers in the adoption of NVIDIA AI platforms.
Responsibilities:
• Enable NVIDIA strategic Telco partners to build enterprise AI solutions on the NVIDIA accelerated computing stack, including NIMs and NeMo microservices.
• Provide deep technical guidance to developers onboarding to NVIDIA AI platforms and SDKs; serve as the primary technical partner and customer point of contact for integration challenges.
• Anticipate partner and customer needs across the adoption lifecycle, identify enablement opportunities that accelerate GenAI utilization, and translate those insights into reference architectures for Agentic AI in Telco—documenting design trade-offs, standard practices, and failure modes, then feeding findings systematically back to product and engineering.
• Advise on high-performance ETL pipeline design for telecom data: scalable, real-time ingestion workflows using NVIDIA Data Acceleration SDKs (RAPIDS, Morpheus) for high-volume telemetry and event streams.
Qualifications:
Required:
• MSc or PhD in Computer Science, Electrical Engineering, Software Engineering, or a related field—or equivalent experience building real systems—with 6+ years developing and deploying AI/ML systems at scale.
• Hands-on experience building enterprise RAG systems with open-source models (LLaMA, Mistral, or similar) and orchestration frameworks like LangChain or LlamaIndex, paired with solid deep learning fundamentals.
• Proficiency in Python, solid understanding of C++, and experience with PyTorch or a comparable deep learning framework.
• Real familiarity with Telco network data—telemetry, logs, SNMP, NetFlow/IPFIX, and time-series streams—paired with hands-on experience across SQL, NoSQL, Elasticsearch, Apache Spark, and Pandas.
• The communication skills to talk technical trade-offs with engineers and outcomes with business partners — often in the same conversation.
Preferred:
• Experience with NVIDIA AI Enterprise software: Morpheus, RAPIDS, NeMo, and NIM.
• Agentic framework fluency: LangGraph, AutoGen, NVIDIA Colang 2.0, or similar multi-agent tools.
• 5G / 6G and O-RAN depth: Next-generation Telco architecture spanning 5GC, Open RAN, network slicing, MEC, and 3GPP standards (Rel. 15–18), combined with O-RAN automation including xApps, rApps, RIC, SDN/NFV, and protocols such as NETCONF, gNMI, and RESTCONF.
• MLOps and DevOps: Kubernetes, Docker, Helm, Jupyter-based automation pipelines.
• Infrastructure awareness around NVIDIA InfiniBand or high-speed Ethernet for distributed model serving.
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.

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About Nvidia

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NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993