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Cuda Remote Jobs (NOW HIRING)

Quantiphi, Inc.

Architect - Platform Engineer

US East/Canada (Remote) Role Overview: We are looking for a highly skilled Architect - Platform ... Enable and optimize the NVIDIA GPU stack (CUDA, cuDNN, NCCL, Triton, RAPIDS, etc.) * Collaborate ...

Workato

Senior AI Research Scientist

San Francisco, CA · On-site +1

$116K - $147K/yr

Quartz ranked us the #1 best company for remote workers Responsibilities We are looking for an ... techniques, and CUDA. Soft Skills / Personal Characteristics * Curiosity‑driven and ...

Nebius

... CUDA, OpenCL). * Customer-centric approach with a proven ability to build trust and foster ... Remote Work Reimbursement: Up to $85/month for mobile and internet. * Disability & Life Insurance:

The Pennsylvania State University

$121K - $231K/yr

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Python, C++, CUDA, time-series analysis, and signal processing * Ability to express yourself and ...

MatX

Software Engineer - Kernels

Mountain View, CA · On-site +1

$175K - $400K/yr

... or GPU/CUDA programming * Language: at least one of assembly, C++, C, Zig, or Rust * This is a ... Remote Perks We work remotely Monday & Friday, supported by home-tech setup, and remote wifi ...

MatX

Runtime Engineer

Mountain View, CA · On-site +1

$175K - $362K/yr

Hands-on with at least one accelerator programming model (CUDA, ROCm, oneAPI Level Zero, TPU, or ... Remote Perks We work remotely Monday & Friday, supported by home-tech setup, and remote wifi ...

Wood Plc

Software Development Engineer

Topeka, KS · On-site +1

NVIDIA, CUDA Python, PyCUDA, etc.) * Field Collection/Mobile Applications (IOS, Android, etc.) and ... Experience with data processing imagery and LiDAR from web services, UAS, or other remote sensing ...

Zoo

CAD Graphics Engine Software Engineer

Los Angeles, CA · On-site +1

$145K - $195K/yr

We are headquartered in Los Angeles, CA with both a local and remote team. We were founded and ... Experience with GPU computing APIs such as CUDA * Strong familiarity of the inner workings of CAD ...

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Cuda Remote information

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How much do cuda remote jobs pay per hour?

As of Jul 11, 2026, the average hourly pay for cuda remote in the United States is $39.36, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $57.45 per hour, depending on experience, location, and employer.

Are CUDA programmers in demand?

CUDA programmers are in high demand in fields such as artificial intelligence, data science, and high-performance computing due to their expertise in parallel programming and GPU acceleration. Companies seek professionals with skills in CUDA, C++, and related tools to optimize computational tasks, and job opportunities are growing across various industries that require intensive data processing. Certifications and experience with GPU architectures can enhance employability in this specialized field.

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

To excel as a CUDA Remote Developer, you need strong programming skills in C/C++ and parallel computing concepts, typically supported by a degree in computer science or related field. Familiarity with NVIDIA CUDA Toolkit, GPU architectures, and related development environments is essential. Excellent problem-solving, communication, and self-motivation skills help you collaborate effectively and manage remote work challenges. These competencies ensure efficient development of high-performance GPU-accelerated applications and productive teamwork in distributed settings.

What are some common challenges faced by Cuda Remote developers when working with distributed GPU workloads?

Cuda Remote developers often encounter challenges related to optimizing data transfer between remote devices, managing synchronization across distributed systems, and debugging performance issues that arise due to network latency. Collaborating with cross-functional teams, such as data scientists and DevOps engineers, is essential to ensure efficient GPU resource allocation and seamless integration with existing infrastructures. Staying up to date with the latest CUDA libraries and best practices is also important for overcoming these hurdles and delivering scalable, high-performance solutions.

What jobs use CUDA?

Jobs that use CUDA typically include roles in GPU programming, machine learning, deep learning, data science, and high-performance computing. These positions often require knowledge of parallel programming, C++, and NVIDIA's CUDA toolkit to optimize software for GPU acceleration.

Does Nvidia offer remote positions?

Nvidia offers remote positions for various roles, including technical and engineering jobs like CUDA Remote. These positions often require specific skills, such as programming in CUDA and experience with GPU computing, and may be available in flexible or fully remote work environments depending on the role and team needs.

What is the difference between Cuda Remote vs Data Analyst?

AspectCuda RemoteData Analyst
Required CredentialsTechnical certifications, remote work experienceDegree in statistics, data science, or related field
Work EnvironmentRemote, often project-basedOffice or remote, depending on employer
Industry UsageTech, finance, healthcareBusiness, marketing, finance
Common Search/ComparisonRemote tech rolesData analysis jobs

While Cuda Remote focuses on remote technical roles often involving CUDA programming, Data Analysts primarily analyze data to inform business decisions. Both roles may require analytical skills, but Cuda Remote emphasizes technical CUDA expertise in remote settings, whereas Data Analysts focus on data interpretation and visualization, often in office or hybrid environments.

What are CUDA Remote jobs?

CUDA Remote jobs are positions that focus on developing, optimizing, or supporting applications using NVIDIA's CUDA platform, which enables parallel computing on GPUs, and can be performed entirely from a remote location. These jobs typically involve programming in C, C++, or Python, and require knowledge of parallel computing concepts. Remote CUDA roles are common in industries like AI, scientific computing, data analytics, and graphics rendering, allowing professionals to collaborate with teams globally without needing to relocate.

How much do CUDA engineers make?

CUDA engineers typically earn between $80,000 and $150,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in GPU programming and deep learning can command higher salaries, especially in tech hubs or companies focusing on AI and high-performance computing.
More about Cuda Remote jobs
What cities are hiring for Cuda Remote jobs? Cities with the most Cuda Remote 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 Cuda Remote jobs? States with the most job openings for Cuda Remote jobs include:
What job categories do people searching Cuda Remote jobs look for? The top searched job categories for Cuda Remote jobs are:
Cuda Remote jobs near you
Infographic showing various Cuda Remote job openings in the United States as of July 2026, with employment types broken down into 50% Full Time, and 50% Contract. Highlights an 100% Remote job distribution, with an average salary of $81,860 per year, or $39.4 per hour.
Architect - Platform Engineer

Architect - Platform Engineer

Quantiphi, Inc.

Remote

Full-time

Posted 14 hours ago

Job description

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
About Quantiphi:
Quantiphi is an award-winning, AI-First global digital engineering company that helps the world's leading Fortune 1000 organizations transform bold ideas into measurable business impact. We go beyond building innovative AI technologies, we solve the problems that matter most to our clients.
Since our founding in 2013, Quantiphi has built a proven track record of turning complex challenges into meaningful outcomes across industries.
Headquartered in Boston, with more than 4,000 professionals worldwide, we partner with global enterprises to deliver large-scale digital, cloud, and AI-driven transformation. #SolvingWhatMatters
We are an Elite and Premier partner to Google Cloud, AWS, NVIDIA, Snowflake, and other leading technology platforms, and our work has been recognized across the industry, including:
  • 3 NVIDIA Partner of the Year awards
  • 3 AWS AI/ML Partner of the Year awards
  • 21x Google Cloud Partner of the Year awards in the past 10 years
  • 3 Snowflake Partner of the Year awards
  • Rated Leaders by Gartner, Forrester, IDC, ISG, Everest Group and other leading analyst firms

Quantiphi delivers First-in-class AI solutions across Life Sciences, Healthcare, Banking, Financial Services, CPG, Manufacturing, Energy, High-Tech, Telecommunications, etc., powered by cutting-edge Generative AI and Agentic AI accelerators.
For more details, visit: Website or LinkedIn Page.
Role:Architect - Platform Engineer
Experience Level:10+ yrs
Work Location:US East/Canada (Remote)
Role Overview:
We are looking for a highly skilled Architect - Platform Engineer to design, optimize, and scale infrastructure for GenAI and LLM workloads. This role is ideal for someone with deep hands-on experience in GPU profiling, distributed training, and high-performance compute environments. You will be working with Architects from other specialties such as Data engineering, Software engineering, ML engineering to create platforms, solutions and applications that cater to latest trends
You'll play a key role in building out GenAI platform foundations, supporting production-grade deployments, and partnering closely with data science, MLOps, and application teams to bring cutting-edge AI solutions to life.
Key Responsibilities:
  • Design and implement scalable infrastructure for LLM and GenAI workloads across multi-GPU environments
  • Perform GPU profiling, benchmarking, and performance optimization for distributed training workloads
  • Manage and schedule compute-intensive jobs using Slurm-based clusters and OpenShift/Kubernetes environments
  • Enable and optimize the NVIDIA GPU stack (CUDA, cuDNN, NCCL, Triton, RAPIDS, etc.)
  • Collaborate with cross-functional teams to deploy models in research and production environments
  • Build and support GenAI pipelines (fine-tuning, RAG, multi-modal inferencing, LLMOps)
  • Develop reusable infrastructure templates using tools like Terraform and Helm
  • Contribute to internal innovation (PoCs, workshops) and support client-facing delivery engagements
  • Develop and deliver automation software required for building & improving the functionality, reliability, availability, and manageability of applications and cloud platforms
  • Champion and drive the adoption of Infrastructure as Code (IaC) practices and mindset
  • Design, architect, and build self-service, self-healing, synthetic monitoring and alerting platform and tools
  • Automate the development and test automation processes through CI/CD pipeline (Git, Jenkins, SonarQube, Artifactory, Docker containers)
  • Build container hosting-platform using Kubernetes
  • Introduce new cloud technologies, tools; processes to keep innovating in the commerce area to drive greater business value.
  • Lead the technical discussion regarding architecture designing and troubleshooting with the clients and provide solutions proactively as required

Basic Qualifications:
  • Strong experience with Slurm and distributed training environments
  • Hands-on expertise with Red Hat OpenShift and/or Kubernetes
  • Deep knowledge of the NVIDIA GPU ecosystem (CUDA, cuDNN, NCCL, Nsight, Triton/TensorRT)
  • Strong foundation in Linux systems, performance tuning, and multi-GPU optimization
  • Experience deploying GenAI workloads (LLM fine-tuning, RAG pipelines, multi-modal systems)
  • Familiarity with Infrastructure-as-Code tools (Terraform, Ansible)
  • Experience with cloud GPU environments (GCP, Azure, AWS, OCI) and/or on-prem GPU clusters
  • Serve as a mentor or guide for senior resources / team leads.
  • Lead the technical discussion regarding architecture design

Other Qualifications (OQs):
  • Experience with NVIDIA NIMs, DGX systems, or GPU-accelerated containers
  • Knowledge of LLMOps frameworks and MLOps integration
  • Familiarity with vector databases and retrieval systems for RAG architectures
  • Comfortable working in client-facing environments and collaborating with AI solution teams

Healthcare Domain Experience (Nice to Have):
  • Experience working with FHIR R4, HL7 v2, or SMART on FHIR
  • Integration with EHR systems (e.g., Epic)
  • Understanding of HIPAA compliance and healthcare data privacy
  • Exposure to clinical workflows, CDS Hooks, or patient-facing applications
  • Experience building clinical decision support systems or healthcare interoperability solutions

What's in it for YOU at Quantiphi:
  • Make an impact at one of the world's fastest-growing AI-first digital engineering companies.
  • Up-skill and discover your potential as you solve complex challenges in cutting-edge areas of technology alongside passionate, talented colleagues.
  • Work where innovation happens - work with disruptive innovators in a research-focused organization with 60+ patents filed across various disciplines.
  • Stay ahead of the curve, immerse yourself in breakthrough AI, ML, data, and cloud technologies and gain exposure working with Fortune 500 companies.

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

Apply