NVIDIA is seeking Senior Application Engineer for technical collaboration on Materials and Chemical Discovery using AI. Sr Application Engineers are drawn from elite developers and scientists who enjoy working with the latest in GPU hardware and AI Models. An ideal candidate is someone who is entrepreneurial, self-motivated, creative and passionate about bringing the latest techniques to customers who want to accelerate the discovery of novel materials using Predictive AI or Generative AI. Discovery of new materials and chemicals is one of the core workloads across a broad range of customers including supercomputing, higher education, manufacturing, semiconductors, agriculture, etc.
As a Sr. Application Engineer, you will be part of the team comprising Product Managers and Strategic Alliance Partners and working with customers.
What you will be doing:
Work directly with developers and researchers who are building, fine-tuning or optimizing AI models for Chemistry and Material discovery.
Collaborate with publishers of open-source applications, datasets, frameworks used for AI Driven Chemical and Materials discovery and display their ability to use NVIDIA ALCHEMI.
Profile, benchmark and suggest optimization strategies to developers building AI models and Agentic AI workflows for discovering novel materials and formulations.
Present at workshops as the domain expert.
What we need to see:
Degree in Chemistry, Material Science or related field (Ph.D. or Masters preferred) or equivalent experience.
4+ years of experience with developing or using AI models for chemistry and material discovery using popular deep learning frameworks on CPUs and GPUs.
Proven ability to benchmark and compare domain specific AI Models for Materials discovery.
Strong written and oral communication skills with the ability to effectively articulate the value proposition to technical and non-technical audiences
Ways to stand out from the crowd:
Experience with using AI frameworks e.g PyTroch, JAX
Background in the development of chemistry/materials simulation software packages, machine learning interatomic potentials (MLIP) design, or generative AI for chemistry/material science.
Knowledge about NV GPU and CUDA- X libraries.