Nvidia Solutions Architect Healthcare Life Sciences 

United States, Texas 

88816024

What you'll be doing:

• Guide customers through the end-to-end process of AI adoption—from requirements gathering and proof-of-concept development to deployment, integration, and ongoing optimization.

• Design, develop, and optimize solutions tailored for healthcare and life science applications, such as AI scientist, autonomous lab, intelligent diagnostic tools, and clinical agents.

• Architect and implement generative AI workflows for use cases including synthetic data generation for biological modalities, domain-adapted pretraining of foundation LLMs, finetuning reasoning models, and orchestration of multi-agent LLM systems using NVIDIA’s GPU-accelerated platforms.

• Keep up to date on AI advancements in healthcare, including multi-modal biology models, virtual cell platforms, and clinical prediction models for patient identification and precision medicine.

• Develop proof-of-concept demonstrations showcasing how NVIDIA’s technology accelerates healthcare innovations.

• Engage with healthcare executives, IT managers, data scientists, clinicians, and developers to promote the adoption of AI-powered healthcare applications.

• Share your findings through training sessions, whitepapers, or blog posts.

• Some travel may be required for on-site customer engagements.

What we need to see:

• MS, PhD or equivalent experience in Computer Science, Biomedical Engineering, Computational Biology, or related fields with strong applied experience.

• 5+ years of experience in software development related to AI/ML in healthcare or life sciences.

• Deep experience with end-to-end generative AI solutions: data ingestion, preprocessing, model training, agentic tool development, pipeline deployment and evaluation.

• Proficiency in Python and AI/ML frameworks (PyTorch, Langchain, or building custom framework) .

• Experience deploying and scaling agentic AI solutions in cloud environments (AWS Bedrock, Azure AI foundry, Vertex AI, etc).

• Excellent communication skills with the ability to present complex technical concepts to both technical and non-technical audiences.

Ways to stand out from the crowd:

• Experience building, deploying, and optimizing agentic AI systems for healthcare and life sciences.

• Understanding basic biomedical concepts and modalities, such as sequence, structure, function, and clinical phenotypes.

• Familiarity with AI deployment/inference technologies such as TensorRT, TRT-LLM.

• Established thought leadership through publications or presentations on AI/ML applications in healthcare and life science.

• Experience collaborating with pharma, techbio, and healthcare providers. Passionate about improving patient outcomes through innovative solutions.