> Markdown version of [/jobs/ext/4316342-senior-software-engineer-md-simulation-engineering](https://www.wearedevelopers.com/jobs/ext/4316342-senior-software-engineer-md-simulation-engineering). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer - MD Simulation Engineering - **Company:** NVIDIA Corporation - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Salary:** $184,000.0 - $287,500.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Computational Biology, Nvidia CUDA, Computer Graphics, Continuous Integration, General-Purpose Computing on Graphics Processing Units, Open Source Technology, Software Architecture, Regression Testing, Scientific Computating, Simulation Software, Software Engineering, High Performance Computing, Gpu Programming, Information Technology, Software Library - **Published:** October 11, 2026 - **Apply:** https://www.careerboard.com/us/en/find-jobs-in-United-States/-498010AF35B64B8274/ ## About the Role * 8+ years of software engineering experience with a strong background in CUDA and GPU programming. * Deep proficiency in C and C+; comfort navigating and chipping in to large, sophisticated codebases. * Strong foundation in high-performance computing * Familiarity with molecular dynamics simulation concepts * Experience building or supplying to scientific software libraries, simulation engines, or developer-facing GPU APIs. * BS/MS in Computer Science, Computational Science, Physics, Applied Mathematics, or a related field, or equivalent experience. Ways to Stand Out from the Crowd: * You have supplied to or deeply used a major MD simulation engine * Experience with GPU compiler toolchains, Kernel delivery mechanisms * Hands-on knowledge of SPME, Ewald summation, or other long-range electrostatics methods at the implementation level. * PhD or equivalent experience in computational chemistry, biophysics, mathematical modeling, or computer science with a focus on HPC or scientific computing. * Experience with mixed-precision or tensor-core-aware algorithm build for scientific workloads as well as contributions to open-source MD simulation or GPU computing projects. ## Description NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique Legacy of innovation that's fueled by great technology-and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA BioNeMo is building the computational foundation for the next generation of biological discovery. We are looking for a Senior Software Engineer to join our MD Simulation Engineering team, whose mission is to enable biological simulation engines at scale. This team builds the GPU-native simulation software that powers molecular dynamics at scale. We work at the intersection of GPU computing and computational biology - delivering high-performance math primitives that simulation software depends on to fully exploit NVIDIA hardware across GPU generations. The work spans Kernel engineering, software architecture, and direct collaboration with the MD simulation ecosystem. If you want to define how scientific simulation is accelerated on modern hardware and see your work in the hands of researchers worldwide, this is the role. What You Will Be Doing: * Build, implement, and optimize CUDA kernels for core MD simulation primitives * Be responsible for the end-to-end delivery of GPU-accelerated simulation math to external partners and the broader MD ecosystem * Integrate simulation primitives into major MD engines * Drive CI/CD infrastructure for multi-SKU Kernel builds, automated performance regression testing, and cross-simulator validation across NVIDIA GPU generations. * Collaborate with Applied Science teams to evaluate new algorithms and translate research prototypes into production-quality, shipped software.