24 of 24 Remote Permanent CUDA Jobs

OpenGL, Vulkan or shaders); CI experience (CMake, JIRA, Git, Jenkins); GIS development tools (GDAL API, MapBox API); multithreading/parallel computing (GPU programming or CUDA); MATLAB/Python scripting for mathematical/geology problems would be advantageous. Due to specific requirements, applicants without the relevant project experiences will not More ❯

OpenGL, Vulkan or shaders); CI experience (CMake, JIRA, Git, Jenkins); GIS development tools (GDAL API, MapBox API); multithreading/parallel computing (GPU programming or CUDA); MATLAB/Python scripting for mathematical/geology problems would be advantageous. Due to specific requirements, applicants without the relevant project experiences will not More ❯

Agile events and activities. Team Technologies used include Python, Conda, Behavior Driven Development (PyTest-BDD, Cucumber), Gherkin, Ubuntu, Docker, Jenkins, Bash, Groovy, C++/CUDA, JIRA, and Github. Work schedule is flexible, but some intersection with team members in different timezones will be required (two regular meetings per week More ❯

topics Familiarity with the AI/ML hardware stack (e.g., GPUs, TPUs, data center design) Familiarity with the AI/ML software stack (e.g., CUDA, PyTorch, TensorFlow, Ray) Experience working on AI research, ML model training, or model deployment Experience with securing AI systems Education Requirements RAND is hiring More ❯

topics Familiarity with the AI/ML hardware stack (e.g. GPUs, TPUs, data center design) Familiarity with the AI/ML software stack (e.g. CUDA, PyTorch, TensorFlow, Ray) Experience working on AI research, ML model training, or model deployment Experience with securing AI systems Education Requirements RAND is hiring More ❯

containerized environments. Software architecture experience Experience developing algorithms in MATLAB or converting MATLAB algorithms to C++ General Purpose Graphical Processing Unit (GPU) OPENCL or CUDA development. Cloud Native Technologies experience (e.g. Kubernetes, Harbor, Helm, etc.) RF, Radar, EO/IR, Electronic Warfare, Signal Processing or Software Defined Radio experience. More ❯

definitions Test frameworks and test development (not test-driven development) Microservices architecture/containerisation (development of containerised plugins, with potential to replace existing components) CUDA integration (AI/ML) Development of new applications to meet user expectations within formal constraints, including HMI/GUI/UX experience Familiarity with More ❯

medical device development Technical Expertise: Experience with multi-tasking systems (real-time preferable) and familiarity with signal processing or AI/ML applications using CUDA on GPUs (preferred), medical device communications protocols (HL7, FHIR) Development Approach: Knowledge of agile methodologies and best practices in software development Tools & Practices: Proficiency More ❯

development Machine-to-machine networking, working to third-party interface definitions Test frameworks and test development (not test-driven development) Microservices architecture/containerisation CUDA integration (AI/ML) Development of new applications to meet user expectations and within formal constraints. HMI/GUI/UX experience needed. Familiarity More ❯

not test-driven development) Microservices architecture/containerisation (needs funding but we can develop containerised plugins going forward and replace existing in slow-time) CUDA integration (AI/ML) Development of new applications to meet user expectations and within formal constraints. HMI/GUI/UX experience needed. Familiarity More ❯

complex machine learning algorithms into scalable, production-quality code, with proficiency in Python and a strong understanding of optimization techniques (experience with Cython and CUDA is a plus). Experience in developing Large Language Models (LLMs) is advantageous. In-depth understanding of computer architecture and its implications on AI More ❯

ML frameworks. Experience optimizing deep learning performance on accelerator hardware. Solid knowledge of deep learning algorithms and compute patterns. Strong programming skills in C++, CUDA, or OpenCL. Background in performance profiling and optimization. BS/MS in Computer Science, Electrical Engineering, or a related field. Interested? Send your CV More ❯

Background: Experience in highly regulated industries, preferably in medical device development. Technical Expertise: Experience with multi-tasking systems, Linux and RTOS, FPGAs, micro-controllers, CUDA, communication protocols (e.g. I2C, SPI, UART, USB, Ethernet, PCIe), driver development and familiarity with signal processing using GPU (preferred). Development Approach: Knowledge of More ❯

AI/ML in the sports domain to create insights or data. Advanced systems knowledge, such as: Developing GPU kernels or ML compilers (e.g., CUDA, OpenCL, TensorRT Plugins, MLIR, TVM ). System optimization for latency and utilization , using tools like Nvidia NSight . Working with embedded SoCs (e.g., Nvidia More ❯

AI/ML in the sports domain to create insights or data. Advanced systems knowledge, such as: Developing GPU kernels or ML compilers (e.g., CUDA, OpenCL, TensorRT Plugins, MLIR, TVM ). System optimization for latency and utilization , using tools like Nvidia NSight . Working with embedded SoCs (e.g., Nvidia More ❯

Sports tech experience: Background applying AI/ML in the sports domain for data generation or insights. Systems optimisation: Knowledge of GPU kernel development (CUDA, OpenCL, etc.), real-time system optimisation (e.g., Nvidia NSight), or experience working with embedded SoCs (Nvidia, Qualcomm, etc.). If you're interested in More ❯

the boundaries of model performance. You'll also work on re-implementing models in an efficient manner by using PyTorch and underlying technologies like Cuda Kernels, Torch compilation techniques. This would include: Evaluating and optimising compute resource usage (e.g., Hopper GPUs) for cost and time efficiency at training and More ❯

you: 3+ years' experience in GPU development Experience developing GPU/AI Kernels Experience engineering for AI/ML workloads Experience with any of: CUDA, OpenCL, HIP, SYCL Knowledge of deep learning algorithms Interested in optimising tough linear algebra equations Knowledge of AI framework internals (PyTorch, TensorFlow, ONNX etc More ❯

Hands-on with monitoring tools like Prometheus and Grafana Nice to have: Experience building Developer Experience (DevX) tools and workflows Familiarity with GPU setups (CUDA, TensorFlow, etc.) Strong networking and network security knowledge Linux/Unix skills and shell scripting A degree in Computer Science or a related field More ❯

Hands-on with monitoring tools like Prometheus and Grafana Nice to have: Experience building Developer Experience (DevX) tools and workflows Familiarity with GPU setups (CUDA, TensorFlow, etc.) Strong networking and network security knowledge Linux/Unix skills and shell scripting A degree in Computer Science or a related field More ❯

the boundaries of model performance. You'll also work on re-implementing models in an efficient manner by using PyTorch and underlying technologies like Cuda Kernels, Torch compilation techniques. This would include: Evaluating and optimising compute resource usage (e.g., Hopper GPUs) for cost and time efficiency at training and More ❯

their implementation in signal processing applications. C++/Python-Based Tools: • Experience with C++/Python-based signal processing tools and libraries. GPU/CUDA Development: • Knowledge of GPU/CUDA development for performance optimization in signal processing applications. Message Queue Implementation: • Experience with message queue implementation and More ❯

to hear from you.) 💡 The Stack & Environment: A diverse, modern environment spanning: Linux, Windows, MacOS, Microsoft 365, Azure AD, Intune, Teams, NICE DCV, Nvidia CUDA, Slurm, Jira Service Desk, Terraform, Azure Resource Manager 💡 What We’re Looking For: 2+ years of experience administering HPC infrastructure Hands-on experience with … Infiniband, Slurm, and GPU compute platforms (e.g. CUDA) Proficiency in systems administration and troubleshooting Strong documentation habits and a customer-focused mindset Experience with VDI solutions and monitoring tools 💡 Bonus Points: Familiarity with Jira Service Desk and Terraform scripting Exposure to SSL management, infrastructure-as-code, or cloud database More ❯

to hear from you.) 💡 The Stack & Environment: A diverse, modern environment spanning: Linux, Windows, MacOS, Microsoft 365, Azure AD, Intune, Teams, NICE DCV, Nvidia CUDA, Slurm, Jira Service Desk, Terraform, Azure Resource Manager 💡 What We’re Looking For: 2+ years of experience administering HPC infrastructure Hands-on experience with … Infiniband, Slurm, and GPU compute platforms (e.g. CUDA) Proficiency in systems administration and troubleshooting Strong documentation habits and a customer-focused mindset Experience with VDI solutions and monitoring tools 💡 Bonus Points: Familiarity with Jira Service Desk and Terraform scripting Exposure to SSL management, infrastructure-as-code, or cloud database More ❯