High Performance Computing Developer
Axle Informatics is a bioinformatics and information technology company that offers innovative computer services, informatics, and enterprise solutions to research centres and healthcare organizations around the globe. With experts in software engineering, bioinformatics and program management, we focus on developing and applying technology tools and techniques to empower decision-making and accelerate the discovery in translational research. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).
We are looking for a developer experienced in both GPU and HPC scaling of computational analysis to support our work at NIH. The position will be based in Bethesda/Rockville, MD. We are looking for a skilled and motivated researcher/developer with expertise in algorithm development and optimization. The successful applicant will be involved with optimizing computational analysis (modern machine learning as well as deep learning solutions) of images and other “big data” acquired in collaboration with scientists, biologists, and/or clinicians across the NIH. A cloud based computational platform is being developed in which heterogeneous compute architectures need to be supported including classical HPC nodes/clusters and modern GPU clusters. Therefore, the ideal applicant will have diverse experience in scaling algorithms in both classic HPC (Spark/C/C++) and GPU (CUDA/OpenCL) environments.
The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.