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.
The expected salary range for this position is between $60,000 to $1,15,000 annually. The actual salary may vary based upon several factors including, but not limited to, relevant skills/experience, time in role, base salary of internal peers, prior performance, business line, and geographic/office location.