Senior Applied Scientist

About the role

We are seeking a Senior Applied Scientist to lead our Machine Learning and Artificial Intelligence R&D efforts. The ideal candidate will leverage deep knowledge of AI principles and techniques to personalize the Qualtrics experience and drive innovation.

Responsibilities

• Leverage deep knowledge of machine learning, natural language processing, and reinforcement learning.
• Develop and optimize scalable and efficient AI applications.
• Tackle challenging problems creatively, using generative models to address real-world use cases.
• Show strong programming skills in Python and proficiency in deep learning frameworks.
• Communicate technical concepts effectively 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.
• Work as part of a multidisciplinary team to research, implement, evaluate, optimize, productize and maintain cutting-edge machine learning models.
• Stay on top of the latest developments in machine learning and related research, and present research findings with the broader community.
• Lead and engage in design reviews, modeling discussions, requirement definitions, and other technical activities in diverse capacity.
• Mentor and grow junior scientists, drive best practices for experimentation, reproducibility, monitoring and lifecycle management, and ensure models are reliable, scalable and impactful in production.
• Champion Evaluation-Driven Development (EDD) by embedding automated testing, risk-based assessments, and production monitoring into the full agentic lifecycle.

Requirements

• Bachelor's and Ph.D. in Computer Science or related fields.
• 2+ years of post-graduate industrial research experience in machine learning, NLP, information retrieval, deep learning or a related field.
• Deep learning implementation expertise (MxNet, TensorFlow, PyTorch etc).
• Excellent communication, writing and presentation skills.
• Excellent command of at least one modern programming language (preferably Python).
• Excellent problem-solving ability.
• Depth in one or more of the following: Natural Language processing, information retrieval, speech processing, deep learning, reinforcement learning, etc.
• Knowledge of or experience in building production-quality and large-scale deployment of applications related to machine learning.
• Comfortable working in a fast-paced, highly collaborative, dynamic work environment.
• Experience in machine learning systems (e.g. SageMaker, MLFlow), and deep learning frameworks (e.g. TensorFlow, PyTorch, MXNet etc).
• Preference for a publication record in top-tier ML and NLP conferences (e.g. NeurIPS, ICML, SIGIR, ICLR, ACL, EMNLP, etc.).
• Proven track record in evaluating complex, multi-turn agentic systems.
• Deep experience with observability tools, evaluating tool-use reliability, and implementing systematic benchmarking in CI/CD pipelines.

Qualifications

• On your resume, highlight your deep knowledge of AI principles, including machine learning, natural language processing, and reinforcement learning.
• Showcase your understanding of both supervised and unsupervised learning techniques and their applications in building intelligent systems.
• Provide examples of how you have developed and optimized algorithms for building scalable and efficient AI applications.
• Describe your experience tackling challenging problems in creative ways, leveraging generative models to address real-world use cases and drive innovation.
• Include evidence of your ability to communicate technical concepts to non-technical stakeholders and gather requirements for AI application development.
• Provide details on your experience designing and executing evaluation strategies for agentic systems, including rubric-based success criteria, multi-turn conversation simulation, and LLM-as-a-judge frameworks.
• Detail your experience working as part of a multidisciplinary team to research, implement, evaluate, optimize, productize and maintain cutting-edge machine learning models.
• Showcase your ability to stay on top of the latest developments in machine learning and related research, and present research findings with the broader community.
• Provide examples of your leadership and engagement in design reviews, modeling discussions, requirement definitions, and other technical activities in diverse capacity.
• Highlight your experience mentoring and growing junior scientists, driving best practices for experimentation, reproducibility, monitoring and lifecycle management, and ensuring models are reliable, scalable and impactful in production.
• Provide examples of your championing of Evaluation-Driven Development (EDD) by embedding automated testing, risk-based assessments, and production monitoring into the full agentic lifecycle.

Skills

• Strong programming skills in Python.
• Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or similar.

Benefits

Qualtrics offers a variety of benefits including wellness reimbursement, an experience bonus, and participation in various employee groups and communities. We also offer a flexible hybrid work model with in-office days and remote work options.

Pay

Details on pay will be provided during the interview process.

Schedule

The role is full-time and requires a regular schedule.