We Are

Synopsys is the leader in engineering solutions from silicon to systems, enabling customers to rapidly innovate AI-powered products. We deliver industry-leading silicon design, IP, simulation and analysis solutions, and design services. We partner closely with our customers across a wide range of industries to maximize their R&D capability and productivity, powering innovation today that ignites the ingenuity of tomorrow.

You Are

You have spent your career making code run faster on hardware that keeps changing. You understand that the difference between a solver that takes three hours and one that takes twenty minutes is not just compute power, it is how the algorithm maps to memory, how threads communicate, and whether someone thought hard about cache locality six months ago. You know your way around a profiler and you can read the output without needing to Google every metric.

Working across CPU and GPU architectures does not intimidate you. You have debugged MPI communication bottlenecks, wrestled with build systems that span multiple platforms, and written code that has to perform consistently whether it is running on a local workstation or a cloud-based HPC cluster. You think in terms of scalability, not just correctness.

Collaboration comes naturally. You can sit with a domain expert who speaks in finite elements and boundary conditions, extract what matters for the code, and turn that into a design spec that your team can actually build from. You care about the engineers downstream who depend on your work holding up under real-world load, not just passing CI.

At Synopsys, you will work on simulation software that shapes how products get designed across industries. The problems are real, the scale is significant, and what you optimize will matter.

What You'll Be Doing

• Design, implement, and optimize parallel programming methods within Ansys Mechanical solver products using MPI, GPU programming models like CUDA, HIP, SYCL, OpenMP, and other HPC frameworks

• Profile solver performance across CPU and GPU architectures using tools like Intel VTune, NVIDIA Nsight, or similar, and translate findings into actionable performance improvements
• Build and maintain code benchmarking suites that track solver performance across releases and catch regressions before they ship
• Drive adoption of modular, hardware-agnostic HPC programming models across multiple solver codebases, working with development teams to ensure consistency and reusability
• Collaborate with numerical methods experts to translate complex algorithmic requirements into performant, maintainable software designs
• Support procurement, configuration, and management of HPC development and testing platforms, including on-premise clusters and cloud-based environments
• Own packaging, build system work, and DevOps tooling using CMake, Azure DevOps, Conan, Docker, or CI/CD pipelines to streamline deployment and testing workflows

The Impact You Will Have

• Reduce solve times for engineering simulations used by leading companies across automotive, aerospace, energy, and electronics industries
• Enable customers to run larger, more complex models by making solvers scale efficiently across hundreds or thousands of cores
• Accelerate the adoption of GPU computing in production simulation workflows, unlocking new performance tiers for users with modern hardware
• Improve developer productivity across multiple solver teams by building reusable HPC frameworks and