Staff Applied Scientist

Qualtrics Qualtrics · Seattle · Seattle, WA · Core AI

Staff Applied Scientist to advance Qualtrics' ML and AI R&D and strategy, focusing on personalizing customer experiences with AI features. The role involves developing and optimizing GenAI applications, conducting rigorous ML modeling (including fine-tuning and customization), and designing sophisticated evaluation strategies for agentic systems. The scientist will also champion Evaluation-Driven Development, ensuring models are reliable, scalable, and impactful in production.

What you'd actually do

  1. Work as part of a multidisciplinary team to research, implement, evaluate, optimize, productize and maintain cutting-edge machine learning models to meet the demands of our rapidly growing business
  2. Stay on top of the latest developments in machine learning and related research, and present research findings with the broader community
  3. Work closely with, and incorporate feedback from other specialists, engineers, and product managers
  4. Lead and engage in design reviews, modeling discussions, requirement definitions and other technical activities in diverse capacity
  5. 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

Skills

Required

  • Leverage your deep knowledge of artificial intelligence (AI) principles, including machine learning, natural language processing, computer vision, 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 GenAI 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 GenAI application development.
  • Design and execute sophisticated evaluation strategies for agentic systems, including defining rubric-based success criteria, multi-turn conversation simulation, and implementing 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.
  • Bachelors and Ph.D in Computer Science or related fields
  • 7+ years of 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
  • Deep understanding of machine learning model life cycle management
  • 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
  • Experience in machine learning systems (e.g. SageMaker, MLFlow), and deep learning frameworks (e.g. TensorFlow, PyTorch, MXNet etc)

Nice to have

  • Preference for a publication record in top-tier ML and NLP conferences (e.g. NeurIPS, ICML, SIGIR, ICLR, ACL, EMNLP, etc.)

What the JD emphasized

  • Deep understanding of machine learning model life cycle management
  • Proven track record in evaluating complex, multi-turn agentic systems.
  • Deep experience with observability tools, evaluating tool-use reliability

Other signals

  • personalize the Qualtrics experience using ML and AI features
  • deliver ML algorithms and models that drive efficiency, innovation, and growth
  • conduct ML modeling with deep expertise and rigor
  • Develop and optimize algorithms for building scalable and efficient GenAI applications
  • Design and execute sophisticated evaluation strategies for agentic systems
  • Champion Evaluation-Driven Development (EDD) by embedding automated testing, risk-based assessments, and production monitoring into the full agentic lifecycle.