About the position
NVIDIA seeks a Product Manager to lead our work in molecular dynamics (MD) and AI-accelerated simulation projects for life sciences. We are interested in finding global authorities and leaders at the intersection of atomistic physics, chemistry, and biology to define and be responsible for the next generation of NVIDIA atomistic software products. You will work with software and hardware developers, research scientists, and the user community to gather requirements, set product roadmaps, and provide go-to-market strategies. This leadership role requires expert knowledge across atomistic simulation, AI, and HPC. Your multidisciplinary expertise in product management, biomolecular MD, AI, and GPU computing will be key to NVIDIA's impact. We need a self-starter to continue growing this area! Do you have the rare blend of technical and product skills? If you are passionate about groundbreaking technology, we would love to learn more about you!
Responsibilities
- Define and champion product vision, strategy, and roadmap for NVIDIA's MD and AI simulation tools in the life sciences.
- Gather insights from key customers, developers, and broader market signals to set requirements and priorities.
- Work closely with engineering leadership to deliver on our product roadmap.
- Engage key customers, academic collaborators, and industry partners to gather insights, validate concepts, and drive adoption.
- Define the go-to-market strategies and contribute to product positioning and sales enablement.
- Work with product marketing to assist in creating technical content that communicates your products' value proposition to the world.
Requirements
- Masters, PhD, or equivalent experience in computational chemistry, biology, or biophysics.
- Deep expertise in biomolecular MD techniques, software packages, and related tools (e.g., DFT, QM/MM).
- Proven understanding of biomolecular AI/ML applications, including simulation, protein folding and design, ligand binding, and drug discovery workflows.
- 8 or more years of product management leadership experience, with proven delivery of software tools, libraries, and SDKs.
- Experience with structure-based deep learning in chemistry and biology, electronic structure theory (e.g., DFT) applications, and hybrid AI+physics methods.
- Outstanding communication and interpersonal skills, with a demonstrated ability to articulate concepts and value propositions to diverse audiences.
Nice-to-haves
- Hands-on contributions to atomistic simulation and AI tooling used by the community.
- Experience with MD applications like FEP workflows and enhanced sampling techniques for biomolecular workflows.
- Understanding of force field development, neural network potentials, ab initio MD, usage, and parameterization.
- Experience in productizing AI and ML models for drug discovery applications.
- Strong experience with NVIDIA GPUs (CUDA) and our HPC+AI software stack.
Benefits
- Equity and benefits.
