About the role
Role Description The NVIDIA AI Engineer - PyCUDA role is a remote contract position focused on building and optimizing GPU-accelerated AI solutions . Day-to-day responsibilities include designing and implementing CUDA/PyCUDA-based algorithms, optimizing neural network models for NVIDIA GPUs, and integrating GPU-accelerated components into production software systems. The engineer will collaborate with data scientists and software developers to deploy scalable AI pipelines for tasks such as pattern recognition and natural language processing, ensuring performance, reliability, and maintainability. Additional responsibilities include profiling and debugging GPU code, contributing to system architecture decisions, and documenting technical designs and best practices for the team.
Qualifications
Strong foundation in Computer Science and Software Development, including proficiency in Python and experience with PyCUDA or CUDA programming. Hands-on experience with Neural Networks and Pattern Recognition, especially in designing and optimizing deep learning models on NVIDIA GPU architectures. Knowledge of Natural Language Processing (NLP) techniques and frameworks, with experience applying them in real-world AI applications. Solid understanding of parallel computing concepts, GPU memory management, and performance profiling tools (e.g., NVIDIA Nsight, CUDA profiler). Experience with modern machine learning frameworks (e.g., PyTorch, TensorFlow) and integrating GPU-accelerated components into production systems. Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent professional experience. Ability to work independently in a remote, contract setting, collaborate effectively with cross-functional teams, and communicate complex technical concepts clearly. Experience with MLOps practices, cloud platforms (e.g., AWS, GCP, Azure), and interest in AI for talent management is an asset.
Not the right fit? Search for PyCUDA Engineer jobs in Canada
About Daisy Intelligence
Daisy is an AI software company that delivers explainable Decisions-as-a-Service for retail merchandise planning and insurance risk management. Daisy’s unique autonomous (no code, no infrastructure, no data scientists, no bias) AI system elevates your employees, enabling them to focus on delivering your mission, servicing your customers, and creating shareholder value. In retail, the Daisy system will deliver promotional item selection, dynamic price optimization for regular and promotional prices, improved demand forecasting and inventory allocation, and optimized assortment plans. For our insurance clients, the Daisy system detects and avoids fraudulent claims while enabling claims automation, minimizing human intervention in claims processing. Daisy’s solutions deliver verifiable financial results with a minimum net income return on investment of 10X.
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About the role
Role Description The NVIDIA AI Engineer - PyCUDA role is a remote contract position focused on building and optimizing GPU-accelerated AI solutions . Day-to-day responsibilities include designing and implementing CUDA/PyCUDA-based algorithms, optimizing neural network models for NVIDIA GPUs, and integrating GPU-accelerated components into production software systems. The engineer will collaborate with data scientists and software developers to deploy scalable AI pipelines for tasks such as pattern recognition and natural language processing, ensuring performance, reliability, and maintainability. Additional responsibilities include profiling and debugging GPU code, contributing to system architecture decisions, and documenting technical designs and best practices for the team.
Qualifications
Strong foundation in Computer Science and Software Development, including proficiency in Python and experience with PyCUDA or CUDA programming. Hands-on experience with Neural Networks and Pattern Recognition, especially in designing and optimizing deep learning models on NVIDIA GPU architectures. Knowledge of Natural Language Processing (NLP) techniques and frameworks, with experience applying them in real-world AI applications. Solid understanding of parallel computing concepts, GPU memory management, and performance profiling tools (e.g., NVIDIA Nsight, CUDA profiler). Experience with modern machine learning frameworks (e.g., PyTorch, TensorFlow) and integrating GPU-accelerated components into production systems. Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent professional experience. Ability to work independently in a remote, contract setting, collaborate effectively with cross-functional teams, and communicate complex technical concepts clearly. Experience with MLOps practices, cloud platforms (e.g., AWS, GCP, Azure), and interest in AI for talent management is an asset.
Not the right fit? Search for PyCUDA Engineer jobs in Canada
About Daisy Intelligence
Daisy is an AI software company that delivers explainable Decisions-as-a-Service for retail merchandise planning and insurance risk management. Daisy’s unique autonomous (no code, no infrastructure, no data scientists, no bias) AI system elevates your employees, enabling them to focus on delivering your mission, servicing your customers, and creating shareholder value. In retail, the Daisy system will deliver promotional item selection, dynamic price optimization for regular and promotional prices, improved demand forecasting and inventory allocation, and optimized assortment plans. For our insurance clients, the Daisy system detects and avoids fraudulent claims while enabling claims automation, minimizing human intervention in claims processing. Daisy’s solutions deliver verifiable financial results with a minimum net income return on investment of 10X.