Senior Applied Research Scientist

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

NVIDIA is seeking senior research scientists to develop foundation models for drug discovery, genomics, proteomics, and chemistry. The role involves designing and training large-scale ML models, experimental design, mentoring, and collaborating with hardware/software teams. Requires a PhD, 2+ years in deep learning/bioinformatics, and expertise in modern AI techniques and life sciences.

What you'd actually do

  1. Designing and training large-scale machine learning models at the intersection of genomics, proteomics, and chemistry
  2. Experimental design for probing the capabilities and limitations of the foundation models that are developed
  3. Mentoring other team members, leading research initiatives, and helping to craft strategic roadmaps
  4. Working closely with hardware and software teams to improve NVIDIA’s platforms for large-scale foundation model applications
  5. Engaging with the broader research community via publications, presentations, and research collaborations

Skills

Required

  • PhD (or equivalent experience) in Computer Science or Computational Biology
  • 2+ years in deep learning, bioinformatics, chemical engineering, structural biology, or related fields.
  • Track record of excellence in engineering and research
  • Deep understanding of modern AI techniques: deep learning for sequences, diffusion models, LLMs, unsupervised learning. Hands-on practical know-how of how to design, train, and evaluate large neural networks.
  • Excellent software engineering and design instincts in Python, C++, or similar.
  • Outstanding expertise in biochemistry, drug discovery, molecular biology, chemical engineering, or related fields

What the JD emphasized

  • Track record of excellence in engineering and research
  • Deep understanding of modern AI techniques: deep learning for sequences, diffusion models, LLMs, unsupervised learning. Hands-on practical know-how of how to design, train, and evaluate large neural networks.
  • Outstanding expertise in biochemistry, drug discovery, molecular biology, chemical engineering, or related fields

Other signals

  • foundation models for life sciences
  • large-scale foundation models
  • deep learning for sequences, diffusion models, LLMs