
Senior Technology Architect
2 weeks ago
As a seasoned technology leader, you will spearhead the design and implementation of cutting-edge GPU computers capable of handling demanding deep learning, high-performance computing, and computationally intensive workloads.
You will be responsible for leading architectural changes and/or exploring novel approaches to accelerate our deep learning models, ensuring they are scalable, efficient, and effective in meeting business needs.
In this role, you will collaborate with various teams to drive an end-to-end workflow from data curation and training to performance optimization and deployment. Additionally, you will oversee task assignment and monitoring to ensure seamless project execution.
Required Skills and Qualifications- Master's or PhD in Computer Science, Electrical Engineering, or related field with strong background in deploying complex deep learning architectures.
- 7+ years of relevant experience in at least a few of the following areas: Machine learning (with focus on Deep Neural Networks), Numerical analysis, Performance analysis, Model compression and Optimization & Computer architecture.
- Strong Data structures and Algorithms know-how with Excellent C/C++ programming skills.
- Hands-on expertise with PyTorch, TensorRT, CuDNN, CUDA, OpenCL, OpenACC, MPI, and OpenMP.
- Proficient in Python programming and bash scripting, as well as Windows, Ubuntu, and CentOS operating systems.
- Excellent communication and collaboration skills, with ability to find creative practical solutions to problems.
As a key member of our technology team, you will have opportunities to contribute to the development of cutting-edge AI solutions that improve efficiency, diagnostic accuracy, and turnaround times in life sciences applications.
Our flexible service model enables swift deployment of custom solutions with minimal resource and time commitment from your side.
About UsOur company provides artificial intelligence-based solutions for Life Sciences applications, leveraging machine and deep learning techniques to develop diagnostic, prognostic, and predictive solutions.
We strive to provide cost benefits in the pharmaceutical domain by speeding up pre-clinical drug development timelines, and enhance efficiency of environmental monitoring required in manufacturing.
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