Principal Software Architect- High Performance Computing

Who We Are

Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips – the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world – like AI and IoT. If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world.

What We Offer

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You’ll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company. Visit our Careers website to learn more.

At Applied Materials, we care about the health and wellbeing of our employees. We’re committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits.

Our Team

Our team is developing a high-performance computing solution for low-latency and high throughput image processing and deep-learning workload that enables our Chip Manufacturing process control equipment to offer differentiated value to our customers.

Your Opportunity

As an architect, you will get the opportunity to grow in the field of high-performance computing, GPU compute infra, complex system design and low-level optimizations for better cost of ownership.

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

Someone who is passionate about and has deep understanding and experience in design and development of cutting edge HPC systems and heterogenous computing infrastructure. He should have very good hands-on experience in parallel programming (CUDA) and AI inference infrastructure. He should be able to multi-task and switch contexts based on business needs.

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.

Additional Information

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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.