Senior Applied AI Researcher, Digital Biology

Responsibilities

• Conceptualize, build, and implement novel deep learning architectures for biological data. Focus on large-scale models like Large Language Models (LLMs), Transformers, and State Space Models (SSMs).
• Develop multimodal learning systems that integrate heterogeneous data types (e.g., clinical time-series, imaging, genomics, and text) for improved representation and prediction.
• Develop both foundational and generative models along with agentic AI systems, encompassing multi-step reasoning, tool use, and autonomous decision-making abilities.
• Develop digital twin systems for healthcare by integrating mechanistic models, physiological data, and AI to simulate disease progression, treatment response, and patient-specific trajectories.
• Implement deep learning systems coordinated with agents, enabling end-to-end workflows that combine learning, planning, and execution.
• Evaluate model performance, analyze results, and iterate on builds to achieve efficient outcomes.
• Apply your knowledge of distributed training to build high-quality code for training, optimizing, and deploying large-scale models, while managing complex datasets.
• Collaborate closely with a diverse team of researchers, bioinformaticians, and domain experts in a highly interdisciplinary environment.
• What We Need to See:
• We are seeking individuals who have a solid background in deep learning and a demonstrated capability to turn innovative concepts into practical, scalable systems.
• Advanced Degree (MS or PhD) in Machine Learning, Computer Science, Engineering, or a related field (or equivalent experience).
• 8+ years of hands-on experience in developing, training, and deploying deep learning models at scale, including LLMs, Transformers, SSMs, and/or generative models.
• Experience with multimodal learning and integrating diverse data modalities is highly valued.
• Experience with agentic AI frameworks or systems (e.g., tool-augmented models, planning-based agents, or multi-agent systems) and strong expertise in distributed training, optimization, and inference.
• Demonstrated capability to conduct independent research, develop effective solutions, and thoroughly assess outcomes.
• Proven history of publications and presentations at leading conferences.
• Solid programming abilities in Python and C++, accompanied by experience in PyTorch and/or CUDA.
• Ways To Stand Out From The Crowd:
• Practical experience developing sophisticated AI systems, including agentic AI (RAG, tools, planning, multi-agent) and multimodal models that integrate vision, language, and structured/time-series data.
• Demonstrated success improving large-scale ML systems, accompanied by experience in data pipelines and distributed frameworks for LLM-scale data.
• Background in bioinformatics or digital biology, with experience working across interdisciplinary teams spanning research, engineering, and clinical domains.
• Experience in developing or deploying digital twin systems, simulation frameworks, or data-driven modeling in healthcare or related fields is a strong plus.
• Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits .
• Applications for this job will be accepted at least until July 3, 2026. This posting is for an existing vacancy.
• NVIDIA uses AI tools in its recruiting processes.

Additional Information

NVIDIA seeks innovative and driven Applied Researchers in deep learning. Ideal candidates possess a proven record of research success and a broad knowledge of artificial intelligence. They bring substantial expertise in machine learning, applied science, and computational medicine. NVIDIA is a global leader in AI-focused high-performance and mobile computing technologies and has ambitious goals for upcoming systems. This position allows you to influence real-world projects in a research-centered team at a dynamic organization. The Applied AI Architecture group focuses on applied research. As a member of the team, you will publish your work and make code available to the community. You will participate in an innovative initiative merging AI with biology. This collaborative effort targets the development of foundational and generative AI models plus agentic AI systems. It strives to deepen our knowledge of complex biological systems and advance diagnostics and scientific discovery. It also enhances NVIDIA's Health Platform ecosystem.

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