Nvidia Solutions Architect - Healthcare 

United States, Texas 

789008701

US, CA, Remote

US, TX, Remote

US, NY, Remote

US, CA, Santa Clara

US, MA, Remote

GPU-accelerated AI systems—including pioneering LLM and generative AI applications. Serving as a trusted technical

What you will be doing:

• Guiding 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, andoptimizesolutions tailored for healthcareand life scienceapplications, suchas AIscientist,autonomouslab, intelligentdiagnostic tools,and clinical agents.

• Architect and implement generative AI workflows forusecases including synthetic data generationforbiologicalmodalities,domain-adapted pretraining of foundationLLMs, fine-tuning reasoning models,andorchestration of multi-agent LLMsystemsusing NVIDIA’s GPU-accelerated platforms.

• Keepup to dateon AI advancements in healthcare, includingmulti-modalbiologymodels, virtual cellplatforms,and clinicalpredictionmodels for patient identification andprecision medicine.

• Develop proof-of-concept demonstrationsshowcasinghow NVIDIA’s technologyaccelerates healthcareinnovations.

• 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, white papers, or blog posts.

• Some travel may berequired

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 experience

• Proventrack recordin software development related to AI/ML in healthcare or life sciences.

• Deep experiencewithend-to-end generative AI solutions: data ingestion,preprocessing, modeltraining, agentictool development,pipelinedeployment and evaluation.

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

• Experience deployingand scalingagenticAI solutions in cloud environments (AWSBedrock, AzureAIfoundry, VertexAI,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, andoptimizingagentic AI systems for healthcareand life sciences.

• Understandingbasic biomedical conceptsand modalities, such as sequence,structure, function, and clinical phenotypes.

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

• Understandingregulatory requirements (e.g., HIPAA) and data privacy concerns specific to healthcare data.

• Established thought leadership through publications or presentations on AI/ML applications inhealthcare and life science as well as experience collaborating withpharma,techbio, andhealthcare providers.Passionate about improving patient outcomes through innovative solutions.