What are the responsibilities and job description for the CUDA Software Developer Healthcare position at Intellectt INC?
Job Details
Job Description & Skill Requirement:
Key Responsibilities:
Design and implement efficient parallel algorithms leveraging CUDA to accelerate processing of large datasets in healthcare applications such as medical imaging, genomics, and predictive analytics.
Work with healthcare data (such as medical images, patient records, and clinical data) to optimize data throughput and reduce processing times, ensuring faster and more accurate results.
Collaborate with data scientists, machine learning engineers, and healthcare professionals to translate complex problems into optimized solutions for high-performance computing environments.
Develop and maintain software frameworks and libraries for GPU-accelerated applications in healthcare.
Conduct performance tuning, profiling, and optimization to maximize the efficiency of CUDA-based applications.
Perform unit and integration testing, troubleshooting, and debugging for GPU-accelerated healthcare solutions.
Stay up-to-date with the latest advancements in GPU computing and CUDA technologies, and identify new opportunities for optimization and innovation.
Document technical specifications, processes, and code to ensure knowledge sharing and maintainability of the codebase.
Ensure that healthcare applications meet regulatory standards for data security, privacy (HIPAA compliance), and patient confidentiality.
Qualifications:
Bachelor's degree in Computer Science, Engineering, or a related field. Master's degree preferred.
3 years of experience in CUDA programming and GPU optimization, with a focus on high-performance computing.
Strong proficiency in C/C and hands-on experience with CUDA programming and profiling tools (e.g., Nsight, Visual Profiler).
Experience with medical imaging libraries (e.g., ITK, VTK, OpenCV) and healthcare-related data processing is a plus.
Solid understanding of parallel computing concepts and performance optimization techniques.
Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or similar, particularly for healthcare applications.
Experience with healthcare data formats (e.g., DICOM, HL7) is a plus.
Strong problem-solving skills, attention to detail, and ability to work in a fast-paced and collaborative environment.
Knowledge of cloud platforms (AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes) is a plus.
Knowledge of healthcare industry standards, including HIPAA regulations, is preferred.
Soft Skills:
Excellent communication and teamwork skills to collaborate with multidisciplinary teams.
Strong analytical and critical thinking capabilities.
Adaptability and a willingness to learn new technologies and tools in the healthcare domain.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
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