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Remote Crowd Compute Jobs (NOW HIRING)

$135K - $181K/yr

As large language models rapidly outgrow the memory and compute budget of any single GPU, this ... Deep understanding of memory hierarchies (GPU HBM, host DRAM, SSD, and remote/object storage) and ...

Senior Software Engineer - Topography

Santa Clara, CA · Remote

$143K - $189K/yr

Familiarity with networking, cluster topology, cloud infrastructure, or large-scale compute systems ... Ways to stand out from the crowd: * Experience with GPU clusters, NVLink, InfiniBand, Ethernet ...

Remote Crowd Compute information

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$14

$20

$28

How much do remote crowd compute jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for remote crowd compute in the United States is $20.95, according to ZipRecruiter salary data. Most workers in this role earn between $18.27 and $23.08 per hour, depending on experience, location, and employer.

What is a Remote Crowd Compute job?

A Remote Crowd Compute job involves performing small tasks or problem-solving assignments over the internet as part of a distributed workforce. These tasks can include data labeling, content moderation, surveys, image categorization, and other microtasks that are broken down and distributed among many remote workers. Crowd compute jobs allow companies to leverage a global workforce to complete large-scale projects efficiently. Workers can typically choose their hours and work from anywhere with an internet connection. It's a flexible way to earn income remotely, suitable for people seeking part-time or supplementary work.

What is the difference between Remote Crowd Compute vs Remote Data Annotator?

AspectRemote Crowd ComputeRemote Data Annotator
Required CredentialsBasic technical skills, sometimes certifications in data handlingAttention to detail, training in annotation tools
Work EnvironmentOnline platforms, flexible hoursOnline, often part-time or project-based
Industry UsageAI training, machine learning projectsData labeling for AI, ML models

Remote Crowd Compute involves managing or coordinating distributed tasks for AI training, often requiring some technical knowledge. Remote Data Annotator focuses on labeling data, typically requiring attention to detail and familiarity with annotation tools. Both roles are remote, part-time, and used in AI and machine learning industries, but they differ in responsibilities and skill requirements.

What are some common challenges faced when working in a remote crowd compute role, and how can they be addressed?

A common challenge in remote crowd compute roles is maintaining clear communication and collaboration with team members across different time zones and backgrounds. To address this, most companies use robust collaboration tools and establish clear guidelines for task management and reporting. Another challenge is staying motivated and productive while working independently; setting a structured routine and actively participating in team forums can help. Regular feedback sessions and virtual team meetings also foster connection and ensure alignment with project goals.

What are the key skills and qualifications needed to thrive as a Remote Crowd Compute worker, and why are they important?

To thrive as a Remote Crowd Compute worker, you need strong digital literacy, attention to detail, and the ability to follow complex instructions, usually with no formal education requirements but sometimes with a preference for prior data entry or annotation experience. Familiarity with online task platforms, spreadsheets, annotation tools, and sometimes basic scripting or data labeling systems is beneficial. Reliability, self-motivation, and effective communication are key soft skills for excelling in a remote, deadline-driven environment. These skills and qualities are essential to ensure high-quality, accurate outputs and successful collaboration in distributed teams.
More about Remote Crowd Compute jobs
What cities are hiring for Remote Crowd Compute jobs? Cities with the most Remote Crowd Compute job openings:
What are the most commonly searched types of Crowd Compute jobs? The most popular types of Crowd Compute jobs are:
What states have the most Remote Crowd Compute jobs? States with the most job openings for Remote Crowd Compute jobs include:
Principal Software Engineer - Large-Scale LLM Memory and Storage Systems

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

Nvidia

Santa Clara, CA • On-site, Remote

$158K - $212K/yr

Full-time

Posted 24 days ago


Nvidia rating

9.3

Company rating: 9.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

15th of 209 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

Hours and flexibility

Workplace

Get the full story on Breakroom


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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