Applied Scientist - Reinforcement Learning and Foundation Models

The Challenge

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 Experience Management (XM) data as a core value proposition and competitive advantage.

As a Machine Learning Applied 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
• Work closely with, and incorporate feedback from other specialists, engineers, and product managers
• Lead and engage in design reviews, modeling discussions, requirement definitions and other technical activities in diverse capacity
• Attend daily stand-up meetings, collaborate with your peers, prioritize features, and work with a sense of urgency to deliver value to your customers

Basic Qualifications 

• Master’s degree Machine Learning, AI or Statistics
• Solid understanding of machine learning fundamentals and tool ecosystem
• 5+ years of combined academic and industrial research experience in machine learning, deep learning, LLMs, foundational models, RL 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

Preferred Qualifications 

• PhD in Computer Science or Statistics with concentration in Machine Learning/AI
• Deep understanding of and research experience with foundation models and reinforcement learning
• Experience in one or more of the following fields: Natural Language processing, information retrieval, speech processing, conversational AI, etc.
• Knowledge of or 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 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. NeurIPS, ICML, SIGIR, ICLR, ACL, EMNLP, etc.)

The base pay range for this position is $133,500 - $246,500 per year; however, base pay offered may vary depending on location, job-related knowledge, education, skills, and experience. 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.