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From Home Cuda Jobs (NOW HIRING)

Mat3ra

Cloud HPC Engineer

Walnut Creek, CA · On-site +1

$130K - $200K/yr

OpenMP/MPI/CUDA (intermediate) * Docker/Singularity or similar (intermediate) Other * ability to ... Work From Home * Free Food & Snacks * Wellness Resources * Stock Option Plan Compensation * $130 ...

Mat3ra

☁ Cloud HPC Engineer ☁

Walnut Creek, CA · On-site

$130K - $200K/yr

OpenMP/MPI/CUDA (intermediate) * Docker/Singularity or similar (intermediate) Other * ability to ... Work From Home * Free Food & Snacks * Wellness Resources * Stock Option Plan Compensation * $130 ...

Mat3ra

☁ Cloud HPC Engineer ☁

Walnut Creek, CA · On-site

$130K - $200K/yr

OpenMP/MPI/CUDA (intermediate) * Docker/Singularity or similar (intermediate) Other * ability to ... Work From Home * Free Food & Snacks * Wellness Resources * Stock Option Plan Compensation * $130 ...

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How much do from home cuda jobs pay per hour?

As of Jun 12, 2026, the average hourly pay for from home cuda in the United States is $16.11, according to ZipRecruiter salary data. Most workers in this role earn between $15.87 and $16.35 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a CUDA Developer, and why are they important?

To thrive as a CUDA Developer, you need a strong background in programming (especially C/C++), parallel computing concepts, and ideally a degree in computer science or a related field. Familiarity with NVIDIA CUDA Toolkit, GPU programming, and performance profiling tools is typically required. Critical thinking, problem-solving, and effective communication skills help in designing efficient algorithms and collaborating with team members. These abilities are crucial to optimize code for high-performance computing applications and deliver scalable solutions.

What is the difference between From Home Cuda vs Data Entry Clerk?

AspectFrom Home CudaData Entry Clerk
Required CredentialsBasic computer skills, sometimes certifications in data managementHigh school diploma or equivalent, basic computer skills
Work EnvironmentRemote, home-basedOffice or remote, depending on employer
Industry UsageFrequent in tech, e-commerce, and digital servicesCommon across various industries like healthcare, finance, retail
Job FocusManaging digital data, software toolsInputting and updating data into systems

From Home Cuda and Data Entry Clerk roles both involve working with digital data, but From Home Cuda typically requires more specialized skills or certifications and is often found in tech-related industries. Data Entry Clerks focus on inputting data and may have fewer certification requirements. Both roles can be remote, but From Home Cuda may involve more complex data management tasks.

What are some common challenges faced by remote CUDA developers, and how can they overcome them?

Remote CUDA developers often encounter challenges such as coordinating with team members across different time zones, ensuring access to high-performance hardware for GPU programming, and maintaining clear communication about code changes and project requirements. To overcome these issues, it's helpful to establish regular check-ins, use collaborative development tools like Git, and leverage cloud-based GPU resources when local hardware is insufficient. Staying proactive with communication and documentation also helps keep projects on track and ensures a smooth workflow.

What are From Home CUDA jobs?

From Home CUDA jobs are remote positions that involve working with CUDA, a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). Professionals in these roles typically work on tasks such as developing, optimizing, and debugging software that leverages GPU acceleration for high-performance computing applications. These jobs can be found in fields like artificial intelligence, machine learning, scientific computing, and graphics processing. Working from home in a CUDA-focused role often requires a strong background in C/C++ programming, experience with GPU architectures, and the ability to collaborate with distributed teams online.
More about From Home Cuda jobs
What cities are hiring for From Home Cuda jobs? Cities with the most From Home Cuda job openings:
What are the most commonly searched types of Cuda jobs? The most popular types of Cuda jobs are:
What states have the most From Home Cuda jobs? States with the most job openings for From Home Cuda jobs include:
What job categories do people searching From Home Cuda jobs look for? The top searched job categories for From Home Cuda jobs are:
From Home Cuda jobs near you
Infographic showing various From Home Cuda job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 1% Hybrid, and 12% Remote job distribution, with an average salary of $33,500 per year, or $16.1 per hour.
System Software Engineer - GPU & Accelerated Compute

System Software Engineer - GPU & Accelerated Compute

Sunday

Redwood City, CA

$211K - $251K/yr

Other

Posted 12 days ago

Job description

Join Us in Building the Future of Home Robotics
At Sunday, we're developing personal robots to reclaim the hours lost to repetitive tasks. We're focused on an ambitious goal to make generalized robots broadly accessible, enabling households to take back quality time.
We have spent the last 18 months building a talented team, securing capital, and validating our technology. We are now seeking passionate individuals to join us in the next phase of our growth. If you are ready to apply your skills to the forefront of robotics innovation, we'd love to hear from you.
What to Expect
The ML & Robotics Infra team builds the foundational systems that every part of our robot perception, ML, controls and behavior runs on, and the developer infrastructure that lets us build, ship, and update that software quickly and safely on every robot in the fleet.
As a System Software Engineer on ML & Robotics Infra focused on GPU and accelerated compute, you'll own how every accelerated workload on the robot from model inference, SLAM/perception, and more gets data, gets scheduled and runs efficiently on shared compute. You'll work alongside teammates who own the runtime and our build and delivery infrastructure, and you'll partner cross-functionally with ML, SLAM/Perception, Controls and Hardware teams to ensure the GPU is a first-class, well-utilized resource that meets the latency and throughput requirements of a real-time robotic system operating in the home.
What You'll Do
You'll own and contribute to the accelerated compute layer of the ML & Robotics Infra, including:
  • Efficient model execution and switching: Reduce gpu kernel launch overheads and make swapping between models on the same device fast and predictable
  • GPU scheduling and time-slicing: Arbitrate GPU access across concurrent users (model inference, SLAM, and other robotics applications) with predictable latency
  • Camera pipeline: Drive low-latency transfer of camera frames into GPU memory, integrating with HW accelerate encode/decode (NVDEC/NVENC) where appropriate
  • CPU GPU data transfer: Build efficient, low-overhead data movement between host and device, including pinned memory, zero-copy paths, and asynchronous transfer patterns
  • CPU/GPU synchronization: Design synchronization primitives and patterns that minimize stalls and keep inference pipelines full
What You'll Bring
  • 2+ years of experience developing gpu systems software
  • Strong proficiency in CUDA and a systems language such as C++, C, or Rust
  • Solid understanding of GPU architecture, GPU workloads, and the tradeoffs involved in time-slicing and sharing the device across users
  • Hands-on experience with the CUDA ecosystem: CUDA runtime API, CUDA Graphs, and CUDA IPC
  • Familiarity with GPU sharing mechanisms such as MPS and MIG
  • Experience with GPU profiling tools such as Nsight Systems and Nsight Compute
  • Solid Linux fundamentals: scheduling, IPC, memory management, and performance tuning
Nice to Have
  • Contributions to CUDA libraries or other GPU programming libraries
  • Experience with camera pipeline integration and NVDEC/NVENC
  • Experience optimizing model inference on embedded GPU platforms (e.g., Jetson)
  • Experience with observability and tracing for GPU-accelerated workloads

At Sunday Robotics, we're building technology shaped by real people - curious, creative, and diverse. We're proud to be an equal opportunity employer and consider all qualified applicants regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Even if you don't meet every single requirement, we encourage you to apply. Studies show that women and underrepresented groups often hold back unless they meet 100% of the criteria - we don't want that to be the reason we miss out on great talent.

Apply