We are looking for a Senior AI Solutions Architect to support our Materials Science & Chemistry accounts - the chemical and advanced-materials companies, battery and energy-materials makers, materials- and chemistry-software vendors, and research labs adopting accelerated computing and AI across materials discovery, molecular design, and chemical-process engineering. In this role you will be a trusted technical advisor to computational chemists, materials scientists, and R&D engineering teams, embedding NVIDIA accelerated computing, NVIDIA ALCHEMI, physics-informed ML, and Generative AI into atomistic simulation, quantum chemistry, process design, and process-simulation workflows. You will play a direct role in improving application performance, compressing discovery and formulation cycles, and establishing the technical foundation required for next-generation materials and chemistry systems.
What you'll be doing:- Support Business Development and Sales teams as part of a small Solutions Architecture team, partnering with Industry Business leads, Account Managers, and Developer Relations managers to drive ecosystem success across Materials Science & Chemistry accounts (chemical and materials companies, battery/energy-materials makers, materials/chemistry ISVs and startups, and research labs).
- Work directly with computational chemists, materials scientists, and customer R&D and engineering teams in a customer-facing setting.
- Help developers GPU-accelerate and scale materials and chemistry workflows - density functional theory (DFT), molecular dynamics (MD), quantum chemistry, machine-learning interatomic potentials (MLIP), high-throughput screening, and generative molecular/materials design - using NVIDIA ALCHEMI and CUDA-X.
- Apply physics-informed ML and surrogate modeling (e.g., NVIDIA PhysicsNeMo) and accelerate computational fluid dynamics and reaction/transport simulation for chemical-process and formulation workflows.
- Apply AI/ML and domain-adapted LLMs to materials and chemistry: property prediction, inverse design, materials informatics, and agentic R&D copilots and knowledge retrieval.
- Analyze materials, chemistry, and process-simulation application architectures and find opportunities for acceleration.
- Provide feedback and collaborate with engineering, product, and research teams.
- Deliver trainings, hackathons, and technical demonstrations on NVIDIA solutions and platforms.
What we need to see:- BS/MS/PhD in Materials Science, Chemistry, Chemical Engineering, Computational/Physical Chemistry, Condensed-Matter or Applied Physics, Computational Science, or a related technical field (or equivalent experience).
- 8+ years in computational materials science or chemistry - atomistic simulation (DFT, MD, Monte Carlo), quantum chemistry, materials informatics, or physics-based process/fluid-dynamics simulation - and/or AI/ML applied to these domains.
- Familiarity with materials/chemistry simulation tools and methods (e.g., VASP, Quantum ESPRESSO, GROMACS, LAMMPS, Gaussian, Schrödinger Suite; DFT, MD, quantum chemistry) and/or machine-learning interatomic potentials (e.g., MACE, NequIP/Allegro) and CFD/reaction-transport for chemical processes.
- Experience in algorithm programming using languages like Python and C/C++, with familiarity GPU-accelerating compute-intensive workloads.
- Development experience using major AI frameworks (e.g., PyTorch, TensorFlow) for scientific ML - graph and equivariant neural networks, generative models, or surrogate modeling.
- Familiarity with accelerated computing platforms, GPU-based distributed systems, and HPC clusters/schedulers (e.g., Slurm).
- Familiarity with containers, numerical libraries, modular software design, version control, GitHub.
- Experience designing, prototyping, and building complex AI/ML-based solutions for customers; able to reason across components such as data pipelines, models, compute, networking, and orchestration.
- Solid written and oral communication skills and familiarity with collaborative environments.
- Team player who can learn, react, and adapt quickly, with an attitude to work in a fast-paced environment.
Ways to stand out from the crowd:- Experience with NVIDIA ALCHEMI, machine-learning interatomic potentials, or GPU-accelerated DFT/MD and quantum-chemistry workflows.
- Experience developing physics-ML and surrogate models (NVIDIA PhysicsNeMo, physics-informed neural networks) or GPU-accelerating CFD and reaction/transport solvers for chemical processes.
- Background with applying domain-adapted LLMs and agentic AI to chemistry and materials R&D (NeMo, NIM microservices, RAG/knowledge retrieval) and generative molecular/materials design.
- Experience with Kubernetes, distributed training, and large-scale inference, including DGX Cloud and Run:ai.
- Background with foundation models for atomistic simulation (e.g., MACE, Orb, UMA) and high-throughput virtual screening, and Omniverse digital twins for chemical-process and fluid-dynamics workflows.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until August 23, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
