Job description
Job Description and Requirements We AreSynopsys 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 AreYou 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 DoingDesign, implement, and optimize parallel programming methods within Ansys Mechanical solver products using MPI, GPU programming models like CUDA, HIP, SYCL, OpenMP, and other HPC frameworksProfile solver performance across CPU and GPU architectures using tools like Intel VTune, NVIDIA Nsight, or similar, and translate findings into actionable performance improvementsBuild and maintain code benchmarking suites that track solver performance across releases and catch regressions before they shipDrive adoption of modular, hardware-agnostic HPC programming models across multiple solver codebases, working with development teams to ensure consistency and reusabilityCollaborate with numerical methods experts to translate complex algorithmic requirements into performant, maintainable software designsSupport procurement, configuration, and management of HPC development and testing platforms, including on-premise clusters and cloud-based environmentsOwn packaging, build system work, and DevOps tooling using CMake, Azure DevOps, Conan, Docker, or CI/CD pipelines to streamline deployment and testing workflowsThe Impact You Will HaveReduce solve times for engineering simulations used by leading companies across automotive, aerospace, energy, and electronics industriesEnable customers to run larger, more complex models by making solvers scale efficiently across hundreds or thousands of coresAccelerate the adoption of GPU computing in production simulation workflows, unlocking new performance tiers for users with modern hardwareImprove developer productivity across multiple solver teams by building reusable HPC frameworks and shared toolingEnsure performance consistency and reliability across solver releases through rigorous benchmarking and regression testingHelp shape the technical direction of Synopsys simulation products as HPC architectures and customer workloads continue to evolveSupport faster iteration cycles for product development teams by streamlining build, test, and deployment infrastructureWhat You'll NeedMinimum Requirements: Bachelor's degree in Mechanical Engineering, Computational Science, Applied Mathematics, Physics, or related field with 2+ years of experience, or Master's degree in a related field. PhD preferred.Strong hands-on experience with HPC software design, testing, and deployment in production or research environmentsSolid understanding of data structures, algorithms, and performance considerations in parallel computing contextsProficiency with Git and collaborative development workflows across distributed teamsProficiency in Fortran and C/C++ for performance-critical code developmentExperience with MPI and distributed memory programming modelsExperience with GPU hardware and at least one GPU programming model such as CUDA, HIP, SYCL/oneAPI, OpenMP, OpenACC, or Kokkos is a strong plusWho You AreYou can look at a profiler trace and identify the bottleneck without needing three meetings to discuss itYou write code that other engineers can pick up six months later without needing you to explain every design choiceYou ask clarifying questions when a requirement is vague rather than guessing and building the wrong thingYou are comfortable managing your own time across multiple priorities and know when to escalate blockers versus solve them yourselfYou can explain a technical tradeoff between two HPC approaches to a domain expert in terms they care about, not just what the benchmark saysYou stay current with HPC architecture trends and programming models without needing to be told, because you care about building software that will still perform well two hardware generations from nowThe Team You'll Be Part OfYou will work within the Ansys Mechanical R&D organization, collaborating with numerical methods experts, solver developers, and other HPC engineers across a geographically distributed team. Your work will directly support the performance and scalability of industry-leading simulation products used by engineers worldwide to design and validate critical systems.Rewards and BenefitsWe offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.#TPG At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability. In addition to the base salary, this role may be eligible for an annual bonus, equity, and other discretionary bonuses. Synopsys offers comprehensive health, wellness, and financial benefits as part of a competitive total rewards package. The actual compensation offered will be based on a number of job-related factors, including location, skills, experience, and education. Your recruiter can share more specific details on the total rewards package upon request. The base salary range for this role is across the U.S.Job Description and Requirements We AreSynopsys 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 AreYou 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 DoingDesign, implement, and optimize parallel programming methods within Ansys Mechanical solver products using MPI, GPU programming models like CUDA, HIP, SYCL, OpenMP, and other HPC frameworksProfile solver performance across CPU and GPU architectures using tools like Intel VTune, NVIDIA Nsight, or similar, and translate findings into actionable performance improvementsBuild and maintain code benchmarking suites that track solver performance across releases and catch regressions before they shipDrive adoption of modular, hardware-agnostic HPC programming models across multiple solver codebases, working with development teams to ensure consistency and reusabilityCollaborate with numerical methods experts to translate complex algorithmic requirements into performant, maintainable software designsSupport procurement, configuration, and management of HPC development and testing platforms, including on-premise clusters and cloud-based environmentsOwn packaging, build system work, and DevOps tooling using CMake, Azure DevOps, Conan, Docker, or CI/CD pipelines to streamline deployment and testing workflowsThe Impact You Will HaveReduce solve times for engineering simulations used by leading companies across automotive, aerospace, energy, and electronics industriesEnable customers to run larger, more complex models by making solvers scale efficiently across hundreds or thousands of coresAccelerate the adoption of GPU computing in production simulation workflows, unlocking new performance tiers for users with modern hardwareImprove developer productivity across multiple solver teams by building reusable HPC frameworks and shared toolingEnsure performance consistency and reliability across solver releases through rigorous benchmarking and regression testingHelp shape the technical direction of Synopsys simulation products as HPC architectures and customer workloads continue to evolveSupport faster iteration cycles for product development teams by streamlining build, test, and deployment infrastructureWhat You'll NeedMinimum Requirements: Bachelor's degree in Mechanical Engineering, Computational Science, Applied Mathematics, Physics, or related field with 2+ years of experience, or Master's degree in a related field. PhD preferred.Strong hands-on experience with HPC software design, testing, and deployment in production or research environmentsSolid understanding of data structures, algorithms, and performance considerations in parallel computing contextsProficiency with Git and collaborative development workflows across distributed teamsProficiency in Fortran and C/C++ for performance-critical code developmentExperience with MPI and distributed memory programming modelsExperience with GPU hardware and at least one GPU programming model such as CUDA, HIP, SYCL/oneAPI, OpenMP, OpenACC, or Kokkos is a strong plusWho You AreYou can look at a profiler trace and identify the bottleneck without needing three meetings to discuss itYou write code that other engineers can pick up six months later without needing you to explain every design choiceYou ask clarifying questions when a requirement is vague rather than guessing and building the wrong thingYou are comfortable managing your own time across multiple priorities and know when to escalate blockers versus solve them yourselfYou can explain a technical tradeoff between two HPC approaches to a domain expert in terms they care about, not just what the benchmark saysYou stay current with HPC architecture trends and programming models without needing to be told, because you care about building software that will still perform well two hardware generations from nowThe Team You'll Be Part OfYou will work within the Ansys Mechanical R&D organization, collaborating with numerical methods experts, solver developers, and other HPC engineers across a geographically distributed team. Your work will directly support the performance and scalability of industry-leading simulation products used by engineers worldwide to design and validate critical systems.Rewards and BenefitsWe offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.#TPG At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability. In addition to the base salary, this role may be eligible for an annual bonus, equity, and other discretionary bonuses. Synopsys offers comprehensive health, wellness, and financial benefits as part of a competitive total rewards package. The actual compensation offered will be based on a number of job-related factors, including location, skills, experience, and education. Your recruiter can share more specific details on the total rewards package upon request. The base salary range for this role is across the U.S.Job Description and Requirements We AreSynopsys 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 AreYou 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 DoingDesign, implement, and optimize parallel programming methods within Ansys Mechanical solver products using MPI, GPU programming models like CUDA, HIP, SYCL, OpenMP, and other HPC frameworksProfile solver performance across CPU and GPU architectures using tools like Intel VTune, NVIDIA Nsight, or similar, and translate findings into actionable performance improvementsBuild and maintain code benchmarking suites that track solver performance across releases and catch regressions before they shipDrive adoption of modular, hardware-agnostic HPC programming models across multiple solver codebases, working with development teams to ensure consistency and reusabilityCollaborate with numerical methods experts to translate complex algorithmic requirements into performant, maintainable software designsSupport procurement, configuration, and management of HPC development and testing platforms, including on-premise clusters and cloud-based environmentsOwn packaging, build system work, and DevOps tooling using CMake, Azure DevOps, Conan, Docker, or CI/CD pipelines to streamline deployment and testing workflowsThe Impact You Will HaveReduce solve times for engineering simulations used by leading companies across automotive, aerospace, energy, and electronics industriesEnable customers to run larger, more complex models by making solvers scale efficiently across hundreds or thousands of coresAccelerate the adoption of GPU computing in production simulation workflows, unlocking new performance tiers for users with modern hardwareImprove developer productivity across multiple solver teams by building reusable HPC frameworks and shared toolingEnsure performance consistency and reliability across solver releases through rigorous benchmarking and regression testingHelp shape the technical direction of Synopsys simulation products as HPC architectures and customer workloads continue to evolveSupport faster iteration cycles for product development teams by streamlining build, test, and deployment infrastructureWhat You'll NeedMinimum Requirements: Bachelor's degree in Mechanical Engineering, Computational Science, Applied Mathematics, Physics, or related field with 2+ years of experience, or Master's degree in a related field. PhD preferred.Strong hands-on experience with HPC software design, testing, and deployment in production or research environmentsSolid understanding of data structures, algorithms, and performance considerations in parallel computing contextsProficiency with Git and collaborative development workflows across distributed teamsProficiency in Fortran and C/C++ for performance-critical code developmentExperience with MPI and distributed memory programming modelsExperience with GPU hardware and at least one GPU programming model such as CUDA, HIP, SYCL/oneAPI, OpenMP, OpenACC, or Kokkos is a strong plusWho You AreYou can look at a profiler trace and identify the bottleneck without needing three meetings to discuss itYou write code that other engineers can pick up six months later without needing you to explain every design choiceYou ask clarifying questions when a requirement is vague rather than guessing and building the wrong thingYou are comfortable managing your own time across multiple priorities and know when to escalate blockers versus solve them yourselfYou can explain a technical tradeoff between two HPC approaches to a domain expert in terms they care about, not just what the benchmark saysYou stay current with HPC architecture trends and programming models without needing to be told, because you care about building software that will still perform well two hardware generations from nowThe Team You'll Be Part OfYou will work within the Ansys Mechanical R&D organization, collaborating with numerical methods experts, solver developers, and other HPC engineers across a geographically distributed team. Your work will directly support the performance and scalability of industry-leading simulation products used by engineers worldwide to design and validate critical systems.Rewards and BenefitsWe offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.#TPGJob Description and RequirementsWe AreSynopsys 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 AreYou 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 DoingDesign, implement, and optimize parallel programming methods within Ansys Mechanical solver products using MPI, GPU programming models like CUDA, HIP, SYCL, OpenMP, and other HPC frameworksProfile solver performance across CPU and GPU architectures using tools like Intel VTune, NVIDIA Nsight, or similar, and translate findings into actionable performance improvementsBuild and maintain code benchmarking suites that track solver performance across releases and catch regressions before they shipDrive adoption of modular, hardware-agnostic HPC programming models across multiple solver codebases, working with development teams to ensure consistency and reusabilityCollaborate with numerical methods experts to translate complex algorithmic requirements into performant, maintainable software designsSupport procurement, configuration, and management of HPC development and testing platforms, including on-premise clusters and cloud-based environmentsOwn packaging, build system work, and DevOps tooling using CMake, Azure DevOps, Conan, Docker, or CI/CD pipelines to streamline deployment and testing workflowsThe Impact You Will HaveReduce solve times for engineering simulations used by leading companies across automotive, aerospace, energy, and electronics industriesEnable customers to run larger, more complex models by making solvers scale efficiently across hundreds or thousands of coresAccelerate the adoption of GPU computing in production simulation workflows, unlocking new performance tiers for users with modern hardwareImprove developer productivity across multiple solver teams by building reusable HPC frameworks and shared toolingEnsure performance consistency and reliability across solver releases through rigorous benchmarking and regression testingHelp shape the technical direction of Synopsys simulation products as HPC architectures and customer workloads continue to evolveSupport faster iteration cycles for product development teams by streamlining build, test, and deployment infrastructureWhat You'll NeedMinimum Requirements: Bachelor's degree in Mechanical Engineering, Computational Science, Applied Mathematics, Physics, or related field with 2+ years of experience, or Master's degree in a related field. PhD preferred.Strong hands-on experience with HPC software design, testing, and deployment in production or research environmentsSolid understanding of data structures, algorithms, and performance considerations in parallel computing contextsProficiency with Git and collaborative development workflows across distributed teamsProficiency in Fortran and C/C++ for performance-critical code developmentExperience with MPI and distributed memory programming modelsExperience with GPU hardware and at least one GPU programming model such as CUDA, HIP, SYCL/oneAPI, OpenMP, OpenACC, or Kokkos is a strong plusWho You AreYou can look at a profiler trace and identify the bottleneck without needing three meetings to discuss itYou write code that other engineers can pick up six months later without needing you to explain every design choiceYou ask clarifying questions when a requirement is vague rather than guessing and building the wrong thingYou are comfortable managing your own time across multiple priorities and know when to escalate blockers versus solve them yourselfYou can explain a technical tradeoff between two HPC approaches to a domain expert in terms they care about, not just what the benchmark saysYou stay current with HPC architecture trends and programming models without needing to be told, because you care about building software that will still perform well two hardware generations from nowThe Team You'll Be Part OfYou will work within the Ansys Mechanical R&D organization, collaborating with numerical methods experts, solver developers, and other HPC engineers across a geographically distributed team. Your work will directly support the performance and scalability of industry-leading simulation products used by engineers worldwide to design and validate critical systems.Rewards and BenefitsWe offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.#TPGWe AreSynopsys 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 AreYou 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 DoingDesign, 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
We Are
We AreWe AreSynopsys 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.
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.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 AreYou AreYou 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.
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.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 aprofilerand 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.
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.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 thathas toperform 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.
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.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 canactually buildfrom. 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.
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.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
What You'll Be DoingWhat 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
The Impact You Will HaveThe 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 shared tooling
- Ensure performance consistency and reliability across solver releases through rigorous benchmarking and regression testing
- Help shape the technical direction of Synopsys simulation products as HPC architectures and customer workloads continue to evolve
- Support faster iteration cycles for product development teams by streamlining build, test, and deployment infrastructure
What You'll Need
What You'll NeedWhat You'll Need- Minimum Requirements: Bachelor's degree in Mechanical Engineering, Computational Science, Applied Mathematics, Physics, or related field with 2+ years of experience, or Master's degree in a related field. PhD preferred.
- Strong hands-on experience with HPC software design, testing, and deployment in production or research environments
- Solid understanding of data structures, algorithms, and performance considerations in parallel computing contexts
- Proficiency with Git and collaborative development workflows across distributed teams
- Proficiency in Fortran and C/C++ for performance-critical code development
- Experience with MPI and distributed memory programming models
- Experience with GPU hardware and at least one GPU programming model such as CUDA, HIP, SYCL/oneAPI, OpenMP, OpenACC, or Kokkos is a strong plus
Who You Are
Who You AreWho You Are- You can look at a profiler trace and identify the bottleneck without needing three meetings to discuss it
- You write code that other engineers can pick up six months later without needing you to explain every design choice
- You ask clarifying questions when a requirement is vague rather than guessing and building the wrong thing
- You are comfortable managing your own time across multiple priorities and know when to escalate blockers versus solve them yourself
- You can explain a technical tradeoff between two HPC approaches to a domain expert in terms they care about, not just what the benchmark says
- You stay current with HPC architecture trends and programming models without needing to be told, because you care about building software that will still perform well two hardware generations from now
The Team You'll Be Part Of
The Team You'll Be Part OfThe Team You'll Be Part OfYou will work within the Ansys Mechanical R&D organization, collaborating with numerical methods experts, solver developers, and other HPC engineers across a geographically distributed team. Your work will directly support the performance and scalability of industry-leading simulation products used by engineers worldwide to design and validate critical systems.
You will work within the Ansys Mechanical R&D organization, collaborating with numerical methods experts, solver developers, and other HPC engineers across a geographically distributed team. Your work will directly support the performance and scalability of industry-leading simulation products used by engineers worldwide to design and validate critical systems.You will work within the Ansys Mechanical R&D organization, collaborating with numerical methods experts, solver developers, and other HPC engineers across a geographically distributed team. Your work will directly support the performance and scalability of industry-leading simulation products used by engineers worldwide to design and validate critical systems.Rewards and Benefits
Rewards and BenefitsRewards and BenefitsWe offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.
We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.#TPG
At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.
At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.In addition to the base salary, this role may be eligible for an annual bonus, equity, and other discretionary bonuses. Synopsys offers comprehensive health, wellness, and financial benefits as part of a competitive total rewards package. The actual compensation offered will be based on a number of job-related factors, including location, skills, experience, and education. Your recruiter can share more specific details on the total rewards package upon request. The base salary range for this role is across the U.S.In addition to the base salary, this role may be eligible for an annual bonus, equity, and other discretionary bonuses. Synopsys offers comprehensive health, wellness, and financial benefits as part of a competitive total rewards package. The actual compensation offered will be based on a number of job-related factors, including location, skills, experience, and education. Your recruiter can share more specific details on the total rewards package upon request. The base salary range for this role is across the U.S.In addition to the base salary, this role may be eligible for an annual bonus, equity, and other discretionary bonuses. Synopsys offers comprehensive health, wellness, and financial benefits as part of a competitive total rewards package. The actual compensation offered will be based on a number of job-related factors, including location, skills, experience, and education. Your recruiter can share more specific details on the total rewards package upon request. The base salary range for this role is across the U.S.
In addition to the base salary, this role may be eligible for an annual bonus, equity, and other discretionary bonuses. Synopsys offers comprehensive health, wellness, and financial benefits as part of a competitive total rewards package. The actual compensation offered will be based on a number of job-related factors, including location, skills, experience, and education. Your recruiter can share more specific details on the total rewards package upon request. The base salary range for this role is across the U.S.- Back to job list