Deep Learning Architect

Job Opportunity:

Responsibilities:

• We seek a leader who will design and implement groundbreaking computer systems that run demanding deep learning, high-performance computing, and computationally intensive workloads.
• The ideal candidate will identify architectural changes and/or completely new approaches for accelerating our deep learning models.
• This person is responsible for converting 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.
• The system architect will benchmark and optimize Computer Vision Algorithms and Hardware Accelerators for performance and quality KPIs.
• This role involves optimizing algorithms for optimal performance on the GPU tensor cores.
• Collaboration with various teams is required to drive an end-to-end workflow from data curation and training to performance optimization and deployment.
• Task assignment and monitoring are also part of this position.

Key Responsibilities:

• Designing and implementing computer systems
• Identifying architectural changes or new approaches for accelerating deep learning models
• Converting business needs into product goals and developing plans for algorithm production-readiness
• Benchmarking and optimizing Computer Vision Algorithms and Hardware Accelerators
• Optimizing algorithms for performance on GPU tensor cores
• Driving end-to-end workflows from data curation to deployment

Requirements:

• Master's or Ph.D. in Computer Science, Electrical Engineering, or related field
• Strong background in deploying complex deep learning architectures
• 7+ years of relevant experience in machine learning, including understanding of DL fundamentals, adapting and training DNNs, and developing code for DNN training frameworks
• Strong Data structures and Algorithms know-how with Excellent C/C++ programming skills
• Hands-on expertise with PyTorch, TensorRT, CuDNN, 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

Desirable Skills:

• 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

About Us:

Our company 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 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.