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. ## Requirements - 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. ## Nice to Have - 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. ## Benefits - Base salary determined based on location, experience, and pay of employees in similar positions. - Base salary range: 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. - Eligibility for equity and benefits. - Applications accepted until July 3, 2026. - NVIDIA uses AI tools in its recruiting processes. - NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.