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Remote Nvidia Deep Learning Jobs in California (NOW HIRING)

Senior LLVM Compiler Engineer

Santa Clara, CA · On-site +1

$121K - $167K/yr

Familiarity with deep learning frameworks and performance‑critical workloads on NVIDIA GPUs With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be ...

Senior Compiler Engineer Infrastructure

Santa Clara, CA · On-site +1

$127K - $173K/yr

Familiarity with deep learning frameworks and performance-sensitive workloads on NVIDIA GPUs With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be ...

AI Safety Engineer

Santa Clara, CA · On-site +1

$90 - $130/hr

As a Machine Learning Engineer, you'll work alongside NVIDIA's research and engineering teams ... Deep understanding of machine learning algorithms, statistical models, and data structures.

AI Safety Engineer

Santa Clara, CA · On-site +1

$90 - $130/hr

As a Machine Learning Engineer, you'll work alongside NVIDIA's research and engineering teams ... Deep understanding of machine learning algorithms, statistical models, and data structures.

AI Security Engineer

Santa Clara, CA · On-site +1

$90 - $130/hr

As a Machine Learning Engineer, you'll work alongside NVIDIA's research and engineering teams ... Deep understanding of machine learning algorithms, statistical models, and data structures.

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Remote Nvidia Deep Learning information

What is the difference between Remote Nvidia Deep Learning vs Remote Machine Learning Engineer?

AspectRemote Nvidia Deep LearningRemote Machine Learning Engineer
Required CredentialsDeep learning certifications, Nvidia GPU expertise, programming skills in Python and CUDAMachine learning certifications, Python, data analysis, model deployment skills
Work EnvironmentRemote, GPU-intensive tasks, AI research, model trainingRemote, data processing, model development, deployment
Industry UsageAI research labs, tech companies, autonomous vehiclesTech firms, finance, healthcare, e-commerce

Remote Nvidia Deep Learning focuses on developing AI models using Nvidia GPUs and CUDA, often in research or AI-specific roles. Remote Machine Learning Engineers work on building and deploying machine learning models across various industries. While both roles require programming and data skills, Nvidia Deep Learning emphasizes GPU expertise and AI research, whereas Machine Learning Engineers focus on broader model deployment and application.

What are the most commonly searched types of Nvidia Deep Learning jobs in California? The most popular types of Nvidia Deep Learning jobs in California are:
What job categories do people searching Remote Nvidia Deep Learning jobs in California look for? The top searched job categories for Remote Nvidia Deep Learning jobs in California are:
What cities in California are hiring for Remote Nvidia Deep Learning jobs? Cities in California with the most Remote Nvidia Deep Learning job openings:
Senior Solutions Architect, GenAI Agentic Networks - Telco

Senior Solutions Architect, GenAI Agentic Networks - Telco

Nvidia

Santa Clara, CA • On-site, Remote

Full-time

Posted 14 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