Applied Scientist II

Seattlefull timeOn Site

mid

H1B: no

Qualtrics Applied Scientist II at Qualtrics develops and optimizes AI and machine learning algorithms to personalize the Qualtrics experience. The role involves building scalable GenAI applications and communicating technical concepts to non-technical stakeholders.

Responsibilities

Leverage deep knowledge of AI principles including machine learning, NLP, computer vision, and reinforcement learning
Use understanding of supervised and unsupervised learning techniques to build intelligent systems
Develop and optimize algorithms for scalable and efficient GenAI applications
Tackle challenging problems leveraging generative models for real-world use cases
Communicate technical concepts to non-technical stakeholders and gather requirements for GenAI development

Qualification

Bachelors and PhExperience with Agentic AI systemsDepth in one or more of the followingComfortable working in a fast paced

Required

Bachelors and Ph.D in Computer Science or related fields
Solid understanding of machine learning fundamentals and tool ecosystem
3+ years of combined academic and industrial research experience in machine learning, NLP, information retrieval, deep learning or a related field.
Experience with Agentic AI systems, including design, development, and rigorous evaluation of agent performance.
Deep learning implementation expertise (TensorFlow, PyTorch etc)
Excellent command of at least one modern programming language (preferably Python)
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
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.)