GPU Development Engineer

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.

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We are seeking an expert GPU programmer to work on our multi-physics computational modeling codes. Your primary responsibility will be to extend the existing parallel processing capabilities in these codes for massive CPU-GPU parallelization. Your initial areas of focus will be models for radiation and ray-tracing particle-tracking chemical kinetics fluid dynamics turbulence heat-transfer plasma physics solid mechanics and their supporting infrastructures especially iterative linear solvers.

Essential Functions / Job Description

Develop CPU-GPU parallelization architectures for different multi-physics modules based on a deep understanding of the underlying solution algorithms data flows and memory usage of each module.

Implement the parallel processing architectures designed for specific modules and ensure high parallel efficiency through profiling optimization and tuning on the full suite of representative application cases.

Re-design refactor and re-write existing Fortran 90 and C/C computational physics modules to prepare them for GPU and hybrid parallelization.

The development work will require involvement in all phases of the development lifecycle including technical requirements definition planning software design software implementation testing support quality assurance extension maintenance and documentation.

Guide and participate in developing long-term roadmaps for hybrid parallelization using MPI CUDA/OpenCL and OpenMP of computational modeling codes at Applied Materials.

Education and Skills / Job Requirements

An or PhD degree in computer science applied mathematics physics or a computational modeling discipline with emphasis on GPU parallelization and programming.

Demonstrable talent and skill in software design development and testing. A high level of skill in profiling debugging and tuning GPU programs.

A high level of proficiency in C/C Python CUDA and OpenCL and a readiness to learn other languages such as Fortran 90.

A high level of proficiency in MPI and OpenMP.

Originality creativity and excellent problem-solving skills.

Desire to learn about different computational physics modeling methods and technologies.

Ability to work independently as well as in close collaboration with other computational scientists.

The successful candidate will be a member of the Computational Products and Solutions Center of Excellence at Applied Materials. You will work with other talented and capable peers developing various modules of our flagship multi-physics software. The work environment is stimulating collaborative and rewarding with good opportunities for learning growth and diversification of expertise and knowledge. You will work on difficult but solvable problems and your work will have a far-reaching impact at Applied Materials and hence on all of humanity. This position is ideal for someone with a passion for scientific computing high-performance computing and taking parallel processing techniques to their limits.

Location

The position is open in Applied Materials offices in Bengaluru or Pune.

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.