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Remote Nvidia Engineering Jobs (NOW HIRING)

Partnering with NVIDIA's software engineering, product, and sales teams to secure design wins and ... We are open to remote work. We look forward to having you join our team! Widely considered to be ...

Partnering with NVIDIA's software engineering, product, and sales teams to secure design wins and ... We are open to remote work. We look forward to having you join our team! Widely considered to be ...

Senior Software and System Architect

OR · Remote

$129K - $175K/yr

... engineer with a real passion for technology, we want to hear from you! #LI-Remote Your base salary ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work ...

Senior Software and System Architect

Santa Clara, CA · Remote

$152K - $206K/yr

... engineer with a real passion for technology, we want to hear from you! #LI-Remote Your base salary ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work ...

Senior Software and System Architect

New York, NY · Remote

$141K - $192K/yr

... engineer with a real passion for technology, we want to hear from you! #LI-Remote Your base salary ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work ...

AI Infra SRE Engineer

San Jose, CA · Remote

$58.25 - $77.50/hr

Remote Duration: Fulltime Must-have * NVIDIA (DGX) or equivalent high-performance-compute (HPC) clusters (e.g. Cray, HPE, IBM) * Cisco UCS C885A * Docker Good to have * DevOps Automation * CI/CD ...

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Remote Nvidia Engineering information

See salary details

$57K

$137K

$197K

How much do remote nvidia engineering jobs pay per year?

As of Jun 12, 2026, the average yearly pay for remote nvidia engineering in the United States is $137,006.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,500.00 and $151,500.00 per year, depending on experience, location, and employer.

What is a Remote Nvidia Engineer?

A Remote Nvidia Engineer is a professional who works for Nvidia, or with Nvidia technologies, from a location outside of a traditional office setting. These engineers may specialize in areas such as GPU development, AI research, software engineering, or hardware design, and they collaborate with teams virtually. Remote Nvidia Engineers use digital tools to communicate, manage projects, and contribute to cutting-edge technologies in graphics processing, artificial intelligence, and computing platforms. The remote aspect allows for flexible work arrangements and the ability to participate in global projects.

What are some common challenges faced by engineers working remotely for Nvidia, and how can they be overcome?

Remote engineers at Nvidia often encounter challenges related to communication across time zones, staying aligned with fast-paced project developments, and maintaining visibility within distributed teams. To overcome these, it's important to proactively engage in virtual meetings, leverage collaboration tools like Slack and Jira, and regularly update your team on progress. Building strong relationships with peers and seeking out mentorship opportunities can also help remote engineers stay connected and advance within the company.

What are the key skills and qualifications needed to thrive as a Remote Nvidia Engineer, and why are they important?

To excel as a Remote Nvidia Engineer, you typically need a strong background in computer engineering, programming (e.g., C++, Python), and experience with GPU architectures, often supported by a relevant degree. Familiarity with Nvidia tools like CUDA, cuDNN, and deep learning frameworks, as well as proficiency in remote collaboration platforms, are crucial. Strong problem-solving skills, self-motivation, and effective communication are vital soft skills for working independently and collaborating across distributed teams. These competencies ensure efficient development, troubleshooting, and innovation in Nvidia's complex, high-performance computing environments.

What is the difference between Remote Nvidia Engineering vs Remote Nvidia Data Scientist?

AspectRemote Nvidia EngineeringRemote Nvidia Data Scientist
Required CredentialsBachelor's in Engineering, Computer Science, or related field; experience with GPU programmingBachelor's or higher in Data Science, Statistics, or related; proficiency in machine learning and data analysis
Work EnvironmentDesign, develop, and optimize GPU hardware/software; collaborative teamsAnalyze large datasets, develop models, and generate insights; often cross-functional teams
Employer & Industry UsagePrimarily in hardware, AI, and high-performance computing sectorsPrimarily in AI, analytics, and research sectors

Remote Nvidia Engineering focuses on hardware and software development for GPUs, requiring engineering credentials and technical skills. Remote Nvidia Data Scientists analyze data and build models, requiring expertise in data science. Both roles are remote, but they serve different functions within Nvidia's ecosystem.

More about Remote Nvidia Engineering jobs
What cities are hiring for Remote Nvidia Engineering jobs? Cities with the most Remote Nvidia Engineering job openings:
What are the most commonly searched types of Nvidia Engineering jobs? The most popular types of Nvidia Engineering jobs are:
What states have the most Remote Nvidia Engineering jobs? States with the most job openings for Remote Nvidia Engineering jobs include:
What job categories do people searching Remote Nvidia Engineering jobs look for? The top searched job categories for Remote Nvidia Engineering jobs are:
Infographic showing various Remote Nvidia Engineering job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $137,006 per year, or $65.9 per hour.
Senior Solutions Architect, GenAI Agentic Networks - Telco

Senior Solutions Architect, GenAI Agentic Networks - Telco

Nvidia

Seattle, WA • On-site, Remote

Full-time

Posted 15 days ago


Job description

We are building the AI systems that will fundamentally change how telecommunications networks are operated - and we want you to help shape that work. As a Senior Solution Architect on our Telco AI team, you will design and deploy Agentic AI applications that automate real carrier operations using the latest generative models, NLP, RAG pipelines, and large-scale distributed systems. We work at the intersection of two fast-moving domains: generative AI and telecommunications infrastructure. That means you will be going deep on both - understanding 5G network data, guiding NVIDIA's strategic Telco partners, and helping engineering teams build things that actually work in production. This is applied work at its most exciting!

What You Will Be Doing:

We are designing, building, and continuously improving agentic LLM applications targeting Telco Network Operations and Autonomous Networks-covering orchestration, tool use, memory, and multi-agent coordination patterns-while evaluating and applying the latest advances in model fine-tuning and customization for telecom-specific corpora including network telemetry, logs, SNMP, NetFlow/IPFIX, and streaming time-series data.

  • 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.

What We Need to See:

We are looking for someone with a strong engineering foundation and genuine curiosity about both AI and networking. Here is what matters most to us:

  • 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.

Ways to Stand Out from the crowd:

These are not requirements - they are signals that you have already been operating in the space we work in every day:

  • 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.

Location & Travel

Preference is for candidates based at NVIDIA HQ. Remote candidates will be considered. Up to 40% travel may be required for on-site customer engagements and industry conferences.

With highly competitive salaries, a comprehensive benefits package, and an excellent engineering work culture NVIDIA is widely considered to be one of the technology industry's most desirable employers! NVIDIA has some of the most innovative people working on meaningful problems that are defining the field of ML/DL, data science, robotics, and graphics.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 31, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Nvidia logo

About Nvidia

Sourced by ZipRecruiter

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