Overview As a Staff Applied Scientist, you apply advanced AI/ML research to build GenAI-powered experiences that differentiate Qualtrics. You will collaborate with cross-functional teams to identify business needs, design scalable AI solutions, and advance evaluation and deployment practices. You'll lead cutting-edge modeling, emphasize explainability and risk-aware production, and mentor colleagues while shaping the AI strategy across product lines. This role offers impact at scale in a global, innovation-driven environment.
Compensation / Benefits- Wellness reimbursement
- Experience bonus
- Hybrid work model ()
- QGroup Communities (MOSAIQ, Green Team, Qualtrics Pride, Q Able, Qualtrics Salute, Women's Leadership Development)
Responsibilities- Research, implement, evaluate, optimize, and productize cutting-edge machine learning models for a fast-growing business
- Stay current with ML developments and present findings to the broader audience
- Collaborate with specialists, engineers, and product managers to incorporate feedback
- Lead design reviews and modeling discussions; define requirements and technical strategies
- Mentor junior scientists, promote best practices for experimentation, reproducibility, and lifecycle management
- Champion Evaluation-Driven Development by embedding automated testing, risk-based assessments, and production monitoring into the agentic lifecycle
Key requirements- 7+ years of industrial research experience in ML, NLP, information retrieval, or related fields
- Deep learning implementation expertise (TensorFlow, PyTorch, etc)
- Excellent communication, writing and presentation skills
- Proficiency in Python or another modern programming language
- Deep understanding of ML model lifecycle management
- Experience building production-quality, large-scale ML deployments
- Knowledge of NLP, information retrieval, speech processing, deep learning, or reinforcement learning
- excellent communication and storytelling to non-technical stakeholders
- problem solving and analytical thinking
- collaboration in cross-functional teams
- AI/GenAI research
- NLP
- information retrieval
