Solutions Architect – Drug Discovery

This is a fully remote position, open to applicants in California, +1 more state.

📋 Description

• Collaborate with business and account teams to gain insight into customer objectives, scientific processes, technical requirements, and strategies for platform adoption.

• Design and enhance AI/ML pipelines for training extensive biological foundation models, with an emphasis on BioNeMo libraries and GPU-accelerated software.

• Create proof-of-concept demonstrations that showcase how NVIDIA software and hardware facilitate scientific breakthroughs.

• Work alongside subject matter experts, engineering, product, and field teams to provide impactful customer solutions.

• Record best practices and educate others through technical enablement, partner training, whitepapers, blogs, internal wiki articles, and interactive customer workshops.

• Act as a trusted technical advisor, incorporating NVIDIA technologies into advanced biopharma and diagnostic applications.

⛳️ Requirements

• MS or PhD in Computational Biology, Computational Chemistry, Computational Physics, Chemical Engineering, Biophysics, Computer Science, or a related technical discipline (or equivalent experience).

• Over 5 years of experience in software development for deep learning, GPU acceleration, or scientific computing applications.

• Practical experience applying ML in at least one area: genomics, quantum chemistry, biomaterials science, or structural biology.

• Experience in profiling and optimizing training workflows for large AI models, including performance tuning, distributed training, data pipelines, and GPU resource utilization.

• Proficiency in Linux environments.

• Experience in HPC or accelerated computing settings, including Slurm and/or Kubernetes-based clusters.

• Strong communication skills for conveying complex technical information to scientists, engineers, executives, and customer stakeholders.

• Enthusiasm for collaborating with innovative customers, continuous learning, and remaining at the cutting edge of AI in life sciences.

• Familiarity with BioNeMo, NeMo, or related NVIDIA frameworks (preferred).

• Experience with Parabricks, RAPIDS-singlecell, ALCHEMI, cuEquivariance, cuEST, or similar accelerated libraries (preferred).

• Background in the pharmaceutical or biotech industries (preferred).

• Customer-facing technical leadership experience, including architecture evaluations, executive briefings, technical workshops, or implementations at key accounts (preferred).

🏝️ Benefits

• Equity

• Benefits