Senior Principal AI Architect
Seattle, Washington, United States
Qualtrics
The Qualtrics Platform and our specialized AI uncovers insights, prioritizes actions, and empowers everyone to improve customer & employee experiences.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 (XM) 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 Principal AI Architect
Why We Have This Role
Qualtrics is on a mission to enhance its leadership in Experience Management (XM) by driving Machine Learning and Artificial Intelligence initiatives. This role supports our commitment to innovation in an evolving landscape of Generative and Agentic AI, enabling us to redefine the boundaries of XM.
How You’ll Find Success
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Leverage Expertise: Utilize your deep knowledge of machine learning algorithms, frameworks, and best practices to drive innovative solutions that meet business challenges.
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Foster Collaboration: Cultivate strong relationships across diverse teams, encouraging open communication and collaboration to amplify the impact of your work and enhance project outcomes.
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Stay Informed: Continuously update your knowledge of the latest advancements in AI and machine learning, ensuring that your approaches are aligned with industry trends and technologies.
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Adapt to Change: Embrace the dynamic nature of the tech landscape by being flexible and agile, proactively addressing challenges and iterating on solutions in response to shifting business needs.
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Communicate Effectively: Clearly articulate complex technical concepts to stakeholders at all levels, ensuring alignment on project goals and facilitating informed decision-making.
How You'll Grow
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Expand Technical Skills: Continuously deepen your expertise in cutting-edge AI and machine learning technologies through ongoing training, workshops, and hands-on experience with new tools and methodologies.
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Engage in Cross-Functional Projects: Take advantage of opportunities to work on diverse, multidisciplinary projects that expose you to different aspects of the business, broadening your understanding of how AI can drive value across various domains.
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Participate in Thought Leadership: Contribute to industry discussions by publishing research, presenting at conferences, or participating in forums, enhancing your professional reputation and establishing yourself as a leader in the AI community.
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Seek Feedback and Reflect Actively seek constructive feedback from peers and leaders to identify strengths and areas for improvement, fostering a habit of self-reflection that promotes continuous personal and professional development.
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Things You’ll Do
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Lead Technical Vision: Spearhead AI initiatives by building large-scale training datasets and designing generative models and agentic platforms.
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Collaborate with Multidisciplinary Teams: Engage with researchers, engineers, and product managers to implement, evaluate, optimize, and maintain cutting-edge machine learning models.
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Strategic Liaison: Act as a technical liaison between the AI team and executive leadership, participating in strategic discussions and technical reviews.
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Research Contributions: Stay updated on the latest machine learning developments and present findings to the broader community
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Daily Agile Operations: Attend stand-up meetings, prioritize features, collaborate with peers, and deliver immediate value to our customers.
What We Are Looking For on Your Resume
- 10+ years of industry and research experience in machine learning.
- Proven ability to build and deploy large-scale, production-quality machine learning applications.
- In-depth understanding of the machine learning model lifecycle management.
- Technical Proficiency: Specialization in areas such as Natural Language Processing, Deep Learning, or Reinforcement Learning; experience with machine learning platforms (e.g., SageMaker, MLFlow) and deep learning frameworks (e.g., TensorFlow, PyTorch).
- Communication Skills: Experience engaging with stakeholders from executives to engineers.
- Mentorship: Background in mentoring and guiding engineers and scientists on complex technical issues.
- Publication Record: A strong history of presentations or publications at major ML conferences (e.g., NeurIPS, ICML, SIGIR, ICLR).
What You Should Know About This Team
The team is composed of highly skilled professionals dedicated to pushing the boundaries of AI and machine learning applications. Our collaborative and fast-paced environment encourages innovation, with a strong focus on quality and delivering impactful solutions.
Our Team’s Favorite Perks and Benefits
- We take pride in our offices design aiming at cultivating creativity from our rooftop views to open and collaborative work spaces
- On top of the standard benefits package (medical, dental, vision, life insurance, etc) we provide snacks, drinks, and free lunches in our office
- We believe in sharing Qualtrics success which is part of the compensation for all employees
For full-time positions, this pay range is for base per year; however, base pay offered may vary depending on location, job-related knowledge, education, skills, and experience. A sign-on bonus and restricted stock units may be included in an employment offer, in addition to a range of medical, financial, and other benefits, based on eligibility criteria.
Washington State Annual Pay Transparency Range$238,000—$434,000 USDTags: Agile Deep Learning Generative modeling ICLR ICML Machine Learning MLFlow ML models NeurIPS NLP PyTorch Reinforcement Learning Research SageMaker TensorFlow
Perks/benefits: Career development Conferences Equity / stock options Health care Insurance Lunch / meals Medical leave Salary bonus Signing bonus Startup environment Team events Transparency
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