Chief GPU Architect

Job Summary

As a seasoned architect, you will be responsible for designing and implementing cutting-edge GPU computers that can handle complex deep learning, high-performance computing, and computationally intensive workloads.

• You will lead the charge in developing innovative solutions to accelerate our deep learning models, including identifying architectural changes and/or completely new approaches.
• With your expertise, you will help us navigate strategic challenges related to compute, networking, and storage design for large-scale, high-performance workloads, effective resource utilization in a heterogeneous computing environment, evolving our private/public cloud strategy, capacity modeling, and growth planning across our products and services.
• As an architect, you are responsible for transforming business needs associated with AI-ML algorithms into a set of product goals covering workload scenarios, end-user expectations, compute infrastructure, and time of execution; this should lead to a plan for making the algorithms production ready.
• Benchmark and optimize computer vision algorithms and hardware accelerators for performance and quality KPIs.
• Optimize algorithms for optimal performance on the GPU tensor cores.
• Collaborate with various teams to drive an end-to-end workflow from data curation and training to performance optimization and deployment.
• Assign tasks to the team and monitor their progress.

• M.S. or Ph.D. in Computer Science, Electrical Engineering, or a related field with a 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 a focus on deep neural networks), including understanding of DL fundamentals; Experience adapting and training DNNs for various tasks; Experience developing code for one or more of the DNN training frameworks (such as Caffe, TensorFlow, or Torch): 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.
• Hands-on expertise with GPU computing (CUDA, OpenCL, OpenACC) and HPC (MPI, OpenMP).
• In-depth understanding of container technologies like Docker, Singularity, Shifter, Charliecloud.
• Proficient in Python programming and bash scripting.
• Proficient in Windows, Ubuntu, and Centos operating systems.
• Excellent communication and collaboration skills.
• Self-motivated and able to find creative practical solutions to problems.

• Opportunity to work on cutting-edge projects and contribute to the development of innovative solutions.
• Collaborative and dynamic work environment.
• Competitive compensation and benefits package.
• Ongoing training and professional development opportunities.

We are a leading provider of artificial intelligence-based solutions for life sciences applications. Our solutions improve efficiency, diagnostic accuracy, and turnaround times in pathology, microbiology, and ophthalmology workflows across pharmaceutical and healthcare laboratories.

We leverage machine and deep learning techniques to develop diagnostic, prognostic, and predictive solutions. Our solutions provide cost benefits in the pharmaceutical domain by speeding up pre-clinical drug development timelines and enhancing the efficiency of environmental monitoring required in manufacturing.

In healthcare applications, our solutions improve treatment outcomes by aiding disease stratification and enabling management protocols tailored to individual patients. We partner with leading hospitals, pharmaceutical companies, CROs, and research labs around the world.