We are looking for a Solutions Architect to work with AI for Healthcare and Life Sciences in Taiwan, focused on academic society to adopt NVIDIA GPU platform on VLM, Digital Twin, AI, Accelerated Analytics, Simulation, Deep Learning or Machine learning technologies.
Your primary focus is on AI for Sciences with researchers and developers at universities, research institute and labs.
Responsibilities:
- Design and implement GPU-accelerated AI solutions for genomics, proteomics, and drug discovery using BioNeMo, Parabricks, or related frameworks.
- Collaborate with pharmaceutical, biotech, and research partners to co-develop digital-biology workflows leveraging large-scale foundation models.
- Build reusable pipelines for sequence analysis, molecular simulation, and generative design of biomolecules.
- Optimise performance and scalability on NVIDIA GPU clusters and cloud environments.
- Contribute to BioNeMo ecosystem growth through technical enablement, reference implementations, and partner collaboration.
- Lead proof-of-concept and production engagements in RNA analysis, structure prediction, and computational drug discovery.
Requirements:
- Master's degree or Ph.D. in Computational Biology, Bioinformatics, Computer Science, or related field.
- 6+ years of experience in AI, computational biology, or life-sciences R&D.
- Strong background in deep learning and model development with PyTorch or TensorFlow.
- Familiarity with bioinformatics workflows such as variant calling, structural prediction, and molecular docking.
- Demonstrated experience with GPU-accelerated computing or HPC systems.
- Excellent communication and cross-disciplinary collaboration skills.
Nice to Have:
- Hands-on experience with BioNeMo, Parabricks, or CUDA-accelerated life-sciences libraries.
- Knowledge of foundation models for biological sequences, molecular property prediction, or structure generation.
- Familiarity with pharmaceutical R&D data formats (FASTA, BAM/VCF, PDB).
- Demonstrated ability to lead technical initiatives or customer collaborations in life-sciences AI.
XML job scraping automation by YubHub
