Principal Software Architect- High Performance Computing

Roles and Responsibility

• As a Software Architect, you will be responsible for design and implementation of robust, scalable infrastructure solutions combining diverse processors (CPUs, GPUs, FPGAs).
• You will analyze and partition workloads to the most appropriate compute unit, ensuring tasks like AI inference and parallel processing runs on specialized accelerators, while serial tasks run on CPUs.
• You will work closely with cross-functional teams, including Algo engineers, product managers, and business stakeholders, to understand requirements and translate them into architectural/software designs that meet business needs.
• You will be coding and developing quick prototypes to establish your design with real code and data.
• You will be a subject Matter expert to unblock software engineers in the HPC domain.
• You will be expected to profile entire cluster of nodes and each node with profilers to understand bottlenecks, optimize workflows and code and processes to improve cost of ownership.
• Conduct performance tuning and capacity planning, monitoring GPU metrics (e.g., using NVIDIA DCGM) for reliability
• Evaluate and recommend appropriate technologies and frameworks to meet project requirements.
• Lead the design and implementation of complex software components and systems.
• Ensure that software systems are scalable, reliable, and maintainable.
• Your primary focus will be on ensuring that the software systems are scalable, reliable, maintainable and cost effective.

Our Ideal Candidate

Qualifications

• 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.

Additional Qualifications

• Experience in HPC Job-Scheduling and Cluster Management Software (SLURM, Torque, LSF etc.)
• 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.

Relocation Eligible

• Applied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.