Senior AI Solutions Architect - Materials Science and Chemistry

Role Description

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.

• 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.
• 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.

Qualifications

• 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.

Requirements

• 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.

Benefits

• Highly competitive salaries.
• Comprehensive benefits package.
• Equity eligibility.