Applied Scientist

At Qualtrics, we create software the world’s best brands use to deliver exceptional frontline experiences, build high-performing teams, and design products people love. But we are more than a platform—we are the creators and stewards of the Experience Management category serving over 18K clients globally. Building a category takes grit, determination, and a disdain for convention—but most of all it requires close-knit, high-functioning teams with an unwavering dedication to serving our customers.

When you join one of our teams, you’ll be part of a nimble group that’s empowered to set aggressive goals and move fast to achieve them. Strategic risks are encouraged and complex problems are solved together, by passing the mic and iterating until the best solution comes to light. You won’t have to look to find growth opportunities—ready or not, they’ll find you. From retail to government to healthcare, we’re on a mission to bring humanity, connection, and empathy back to business. Join over 5,000 people across the globe who think that’s work worth doing.

Senior Applied Scientist

Why We Have This Role

We are looking for a talented and innovative Senior Applied Scientist to bring our Machine Learning and Artificial Intelligence R&D to the next level. Our goal is to personalize the Qualtrics experience using ML/AI features showcasing Qualtrics data as a core value proposition and competitive advantage. Applied scientists partner with application teams to deliver algorithms and models that drive efficiency, innovation, and growth. They identify business needs and define strategies where Qualtrics can most benefit from AI technologies and they conduct modeling with deep expertise and rigor, including model selection, training, fine-tuning, customization, explainability, and evaluation.

How You’ll Find Success

• Leverage your deep knowledge of AI principles, including machine learning, natural language processing, and reinforcement learning.
• Use your understanding of both supervised and unsupervised learning techniques, and their applications in building intelligent systems.
• Develop and optimize algorithms for building scalable and efficient AI applications.
• Tackle challenging problems in creative ways, leveraging generative models to address real-world use cases and drive innovation.
• Use effective communication skills to articulate technical concepts to non-technical stakeholders and gather requirements for AI application development.
• Design and execute evaluation strategies for agentic systems, including rubric-based success criteria, multi-turn conversation simulation, and LLM-as-a-judge frameworks.
• Show strong programming skills in languages like Python, along with proficiency in deep learning frameworks such as TensorFlow, PyTorch, or similar.