Principal Engineer

You will provide leadership in designing and implementing ground-breaking GPU computers that run demanding deep learning, high-performance computing, and computationally intensive workloads. As an expert, you will help us with the strategic challenges we encounter, including 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 modelling, and growth planning across our products and services. As an architect you are responsible for converting business needs associated with AI-ML algorithms in to a set of product goals covering workload scenarios, end user expectations, compute infrastructure and time of execution; Benchmark and optimise the Computer Vision Algorithms and the 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. MS or PhD in Computer Science, Electrical Engineering, or related field. A strong background in deployment of complex deep learning architectures . ~7+ years of relevant experience in at least a few of the following relevant areas is required in your work history: Machine learning (with 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. ~ 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. ~ Self-motivated and able to find creative practical solutions to problems. Hands-on experience with HPC cluster job schedulers such as Kubernetes, SLURM, LSF. Familiarity with cloud computing architectures Hands-on experience with Software Defined Networking and HPC cluster networking. Working knowledge of cluster configuration management tools such as Ansible, Puppet, Salt. Understanding of fast, distributed storage systems and Linux file systems for HPC workloads. AIRA Matrix provides 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 by enhancing the efficiency of environmental monitoring required in manufacturing. Our clients and partners include leading hospitals, pharmaceutical companies, CROs, and research labs around the world. Our deep learning platforms with existing network models and pre-built AI applications provide the foundation for fast customizations and help tackle any unique challenges in your image analysis and study management workflows. Our flexible service model enables the swift deployment of these custom solutions with minimal resource and time commitment from your side. Our Application Development Team plays an important role in developing competent customer facing applications to access our AI solutions and enterprise-level image management systems in life sciences. -- Talent Acquisition Specialist Website :