Senior Applied Scientist-Conversational AI at Qualtrics
The Qualtrics XM Platform™ is a system of action that helps businesses to attract customers who stay longer and buy more, to engage and empower employees to do the best work of their lives, to develop breakthrough products people love, and to build a brand people can’t imagine living without.
Joining Qualtrics means becoming part of a team bold enough to chase breakthrough experiences - like building a technology that will be a force for good. A team committed to diversity, equity, and inclusion because of a conviction that every voice holds value, with a vision for representation that matches the world around us and inclusion that far exceeds it. You could belong to a team whose values center on transparency, being all in, having customer obsession, acting as one team, and operating with scrappiness. All so you can do the best work of your career.
We believe every interaction is an opportunity. Are we yours?
The mission of the iQ team is to bring intelligence into the Qualtrics platform and products. We build a large suite of analytics tools built directly into the Experience Management (XM) PlatformTM that automatically analyze experience data 24/7 to proactively spot opportunities for improvement, recommend the actions to take and automate the relevant tasks and the actions.
We are looking for talented and innovative applied scientists to bring our Machine Learning and Artificial Intelligence R&D and strategy to the next level. Our goal is to personalize the Qualtrics experience using ML and AI features showcasing Qualtrics data as a core value proposition and competitive advantage.
As a Conversation AI scientist at Qualtrics, you should love building cutting-edge ML models to solve hard customer problems. Crafting models in an agile environment to withstand hyper growth and owning quality from end-to-end is a rewarding challenge and one of the reasons Qualtrics is such an exciting place to work!
In addition, you will:
- 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
- Stay on top of the latest developments in machine learning and related research, and present research findings with the broader community
- Partner closely with, and incorporate feedback from other teams, product specialists, engineers, product managers, executives and other stakeholders
- Lead and engage in design reviews, modeling discussions, requirement definitions and other technical activities in diverse capacity
- Contribute to the long-term vision for Conversational AI within the organization
- MS or Ph.D. in Computer Science or related fields
- 5+ years of research and development experience in one or more of: NLP, NLU, speech processing, information extraction, information retrieval, conversational AI
- 3+ years of combined academic and industrial research experience in state-of-the-art deep learning and statistical modeling techniques, e.g. (e.g., Transformers, BERT, Electra, T5).
- Solid understanding of machine learning fundamentals and tool ecosystem
- 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
- Excellent interpersonal and communication skills
- PhD with 1+ years of experience in one or more of: natural language understanding/processing, speech processing, dialog understanding, text summarization, question answering, knowledge graphs
- Experience with multilingual modeling
- Deep understanding of machine learning model life cycle management
- Experience in building production quality and large scale deployment of applications related to machine learning
- Experience with managing, processing and analyzing large, complex, multi-modal and unstructured datasets
- Comfortable working in a fast paced, highly collaborative, dynamic work environment.
- Experience in mentoring engineers and scientists on complex technical issues
- Experience in machine learning systems (e.g. SageMaker, MLFlow), and deep learning frameworks (e.g. TensorFlow, PyTorch, MXNet etc)
- Strong publication record in top-tier ML and NLP conferences (e.g. ACL, NAACL, EMNLP, NeurIPS, ICML, ICLR, AAAI, SIGIR etc.)