Senior AI Solutions Architect – Materials Science, Chemistry

This is a fully remote position, open to applicants in California, +2 more states.

📋 Description

• Provide support to the Business Development and Sales teams as part of the Solutions Architecture team.

• Collaborate with Industry Business leaders, Account Managers, and Developer Relations managers across Materials Science & Chemistry sectors.

• Offer guidance to computational chemists, materials scientists, and customer R&D and engineering teams.

• Assist developers in leveraging GPU acceleration to enhance and scale materials and chemistry workflows using NVIDIA ALCHEMI and CUDA-X.

• Implement physics-informed machine learning and surrogate modeling techniques, including NVIDIA PhysicsNeMo.

• Facilitate advancements in computational fluid dynamics and reaction/transport simulations for chemical-process and formulation workflows.

• Utilize AI/ML and domain-adapted LLMs to address materials and chemistry challenges.

• Evaluate application architectures and pinpoint opportunities for performance enhancement.

• Work in conjunction with engineering, product, and research teams.

• Conduct training sessions, hackathons, and technical demonstrations on NVIDIA solutions and platforms.

⛳️ Requirements

• BS/MS/PhD in Materials Science, Chemistry, Chemical Engineering, Computational/Physical Chemistry, Condensed-Matter or Applied Physics, Computational Science, or a related technical discipline, or equivalent experience.

• Over 8 years of experience in computational materials science or chemistry, and/or AI/ML relevant to these fields.

• Proficiency with materials/chemistry simulation tools and methodologies, including VASP, Quantum ESPRESSO, GROMACS, LAMMPS, Gaussian, Schrödinger Suite, DFT, MD, and quantum chemistry.

• Knowledge of machine-learning interatomic potentials and CFD/reaction-transport processes for chemical applications.

• Programming experience in Python and C/C++.

• Familiarity with GPU acceleration for compute-intensive tasks.

• Development experience with PyTorch and/or TensorFlow for scientific machine learning applications.

• Understanding of accelerated computing platforms, GPU-based distributed systems, and HPC clusters/schedulers such as Slurm.

• Knowledge of containers, numerical libraries, modular software design, version control, and GitHub.

• Experience in designing, prototyping, and constructing complex AI/ML-based customer solutions.

• Strong written and verbal communication skills.

• Capacity to work collaboratively and adapt quickly in a dynamic environment.

🏝️ Benefits

• Equity.

• Comprehensive benefits package.

• Competitive salary.