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Remote Python Network Programming Jobs in Santa Clara, CA

Solutions Engineer

Santa Clara, CA · On-site +1

$140K - $170K/yr

  • Medical

  • Retirement

  • PTO

... to network, cloud, and application operators. It enables operations teams to meet their KPIs ... Remote and hybrid arrangements are not available for this position. Responsibilities * Serve as a ...

Remote Job Overview We are seeking experienced SolidWorks Specialists to contribute their expertise ... Reverse engineering (Scan-to-CAD). * Manufacturability analysis. * Python, iLogic, and VBA ...

Remote Job Overview We are seeking experienced SolidWorks Specialists to contribute their expertise ... Reverse engineering (Scan-to-CAD). * Manufacturability analysis. * Python, iLogic, and VBA ...

Engineer II

Dublin, CA · On-site +1

$113K - $195K/yr

It involves developing and maintaining Python-based data processing solutions to support scalable ... Ensure secure data handling by applying knowledge of networking, authentication, SSL, certificates ...

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 ... Python * GoLang, C/C++ * Enterprise Grade Kubernetes cluster (RedHat OpenShift - preferred) and/or ...

Inspection Application Engineer

Milpitas, CA · On-site +1

$110K - $150K/yr

Basic coding skills (S+, C++ or python). * Experience of data analysis using S+/R or python ... Ability to work with remote development support to resolve issues at customer site for apps work in ...

Showing results 41-60

Remote Python Network Programming information

See Santa Clara, CA salary details

$15

$68

$101

How much do remote python network programming jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for remote python network programming in Santa Clara, CA is $68.85, according to ZipRecruiter salary data. Most workers in this role earn between $56.73 and $78.22 per hour, depending on experience, location, and employer.

What is a remote Python network programmer?

A Remote Python Network Programmer is a software developer who specializes in building and maintaining networked applications using the Python programming language, while working from a remote location. Their work often involves creating scripts or applications to manage network connections, automate network tasks, handle data transfers, and interact with protocols such as HTTP, TCP/IP, and sockets. These professionals may work on cloud-based systems, APIs, or distributed applications, and are skilled in both Python and networking concepts. Remote roles allow them to collaborate with teams and manage network infrastructure from anywhere in the world.

What are the key skills and qualifications needed to thrive as a remote Python network programmer?

To thrive as a Remote Python Network Programmer, you need strong proficiency in Python, a solid understanding of networking protocols, and experience with network programming concepts, often supported by a degree in computer science or a related field. Familiarity with tools like Wireshark, libraries such as socket and asyncio, and knowledge of version control systems like Git are typically required. Exceptional problem-solving skills, self-motivation, and clear written communication are important soft skills for remote collaboration and troubleshooting. These abilities ensure reliable network solutions, efficient teamwork, and effective project delivery in distributed environments.

How does collaboration typically work for remote Python network programmers working with distributed teams?

Remote Python network programmers often collaborate closely with cross-functional teams using various communication and project management tools. Daily stand-ups, code reviews, and pair programming sessions are commonly conducted over video calls and chat platforms to ensure seamless integration of network applications. Clear documentation and version control (e.g., Git) play a crucial role in keeping everyone aligned, especially when troubleshooting network protocols or deploying updates. The remote setup requires strong self-management skills and proactive communication to address potential challenges, such as debugging network issues across different environments.

What is the difference between Remote Python Network Programming vs Remote Python Web Development?

AspectRemote Python Network ProgrammingRemote Python Web Development
Required SkillsNetworking protocols, socket programming, securityHTML, CSS, JavaScript, frameworks like Django or Flask
Work EnvironmentServer-side, backend infrastructure, network systemsFrontend and backend web applications, cloud hosting
Industry UsageTelecommunications, cybersecurity, cloud servicesE-commerce, media, SaaS platforms
CertificationsNetworking certifications (e.g., CCNA, CompTIA Network+)Web development certifications (e.g., Certified Web Developer)

Remote Python Network Programming focuses on building and maintaining network systems, protocols, and security, often requiring networking certifications. In contrast, Remote Python Web Development centers on creating web applications using Python frameworks, emphasizing frontend-backend integration. Both roles involve Python skills but serve different technical and industry needs.

Principal Software Engineer - Large-Scale LLM Memory and Storage Systems

Nvidia

Santa Clara, CA • On-site, Remote

$158K - $212K/yr

Full-time

Re-posted 26 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 244 rated software companies


Job description

NVIDIA Dynamo is a high-throughput, low-latency inference framework for serving generative AI and reasoning models across multi-node distributed environments. Built in Rust for performance and Python for extensibility, Dynamo orchestrates GPU shards, routes requests, and manages shared KV cache across heterogeneous clusters so that many accelerators feel like a single system at datacenter scale. As large language models rapidly outgrow the memory and compute budget of any single GPU, this platform enables efficient, resilient deployment of cutting-edge LLM workloads.


We are seeking a Principal Systems Engineer to define the vision and roadmap for memory management of large-scale LLM and storage systems.


What you'll be doing:

  • Design and evolve a unified memory layer that spans GPU memory, pinned host memory, RDMA-accessible memory, SSD tiers, and remote file/object/cloud storage to support large-scale LLM inference.

  • Architect and implement deep integrations with leading LLM serving engines (such as vLLM, SGLang, TensorRT-LLM), with a focus on KV-cache offload, reuse, and remote sharing across heterogeneous and disaggregated clusters.

  • Co-design interfaces and protocols that enable disaggregated prefill, peer-to-peer KV-cache sharing, and multi-tier KV-cache storage (GPU, CPU, local disk, and remote memory) for high-throughput, low-latency inference.

  • Partner closely with GPU architecture, networking, and platform teams to exploit GPUDirect, RDMA, NVLink, and similar technologies for low-latency KV-cache access and sharing across heterogeneous accelerators and memory pools.

  • Mentor senior and junior engineers, set technical direction for memory and storage subsystems, and represent the team in internal reviews and external forums (open source, conferences, and customer-facing technical deep dives).

What we need to see:

  • Masters or PhD or equivalent experience

  • 15+ years of experience building large-scale distributed systems, high-performance storage, or ML systems infrastructure in C/C++ and Python, with a track record of delivering production services.

  • Deep understanding of memory hierarchies (GPU HBM, host DRAM, SSD, and remote/object storage) and experience designing systems that span multiple tiers for performance and cost efficiency.

  • Distributed caching or key-value systems, especially designs optimized for low latency and high concurrency.

  • Hands-on experience with networked I/O and RDMA/NVMe-oF/NVLink-style technologies, and familiarity with concepts like disaggregated and aggregated deployments for AI clusters.

  • Strong skills in profiling and optimizing systems across CPU, GPU, memory, and network, using metrics to drive architectural decisions and validate improvements in TTFT and throughput.

  • Excellent communication skills and prior experience leading cross-functional efforts with research, product, and customer teams.

Ways to stand out from the crowd:

  • Prior contributions to open-source LLM serving or systems projects focused on KV-cache optimization, compression, streaming, or reuse.

  • Experience designing unified memory or storage layers that expose a single logical KV or object model across GPU, host, SSD, and cloud tiers, especially in enterprise or hyperscale environments.

  • Publications or patents in areas such as LLM systems, memory-disaggregated architectures, RDMA/NVLink-based data planes, or KV-cache/CDN-like systems for ML.

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our special engineering teams are growing fast. If you're a creative and autonomous engineer with a genuine passion for technology, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until January 13, 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.

What Nvidia employees say

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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