Design and implementation of robust, scalable infrastructure solutions combining diverse processors (CPUs, GPUs, FPGAs)
Analyze and partition workloads to the most appropriate compute unit
Ensure tasks like AI inference and parallel processing runs on specialized accelerators
Work closely with cross-functional teams to understand requirements
Translate requirements into architectural/software designs
Code and develop quick prototypes
Profile entire cluster of nodes and each node to understand bottlenecks
Conduct performance tuning and capacity planning
Monitor GPU metrics for reliability
Evaluate and recommend technologies and frameworks
Lead the design and implementation of complex software components and systems
Ensure that software systems are scalable, reliable, and maintainable.

12 to 18 years of experience in implementing robust, scalable, and secure infrastructure solutions combining diverse processors (CPUs, GPUs, FPGAs)
Working experience of GPU inference server like Nvidia Triton
Very good knowledge C/C++, Data structure and Algorithms and complexity analysis
Experience in developing Distributed High Performance Computing software using Parallel programming frameworks like MPI, UCX etc.
Experience in GPU programming using CUDA, OpenMP, OpenACC, OpenCL etc.
In depth experience in Multi-threading, Thread Synchronization, Inter process communication, and distributed computing fundamentals
Experience in Inter Process communication using Shared memory and Pipes
Experience in performance profiling at application and system level (e.g. vtune, Oprofiler, perf, Nividia Nsight etc.)
Experience in low level code optimization techniques using Vectorization and Intrinsics, cache-aware programming, lock free data structures etc.
Familiarity with microservices architecture and containerization technologies (docker/singularity) and low latency Message queues
Excellent problem-solving and analytical skills
Strong communication and collaboration abilities
Ability to mentor and coach junior team members
Experience in Agile development methodologies
Good knowledge of Low-latency and high-throughput data transfer technologies (RDMA, RoCE, InfiniBand)
Good Knowledge of Parallel processing and DAG execution Frameworks like Intel TBB flowgraph, OpenCL/SYCL etc.

Principal Software Architect – High Performance Computing

Key skills