The company is looking to advance its AI technologies and develop AI-powered features for the Experience Management Platform.
Requirements
- Solid understanding of machine learning and AI engineering fundamentals and tool ecosystem with deep and demonstrable expertise in at least one topic or application of machine learning
- Familiarity with relevant technology stacks such as deep learning frameworks (TensorFlow, PyTorch, etc) and ML platforms such as SageMaker, VertexAI etc
- Technical depth in machine learning systems (e.g. SageMaker, MLFlow), and deep learning frameworks (e.g. TensorFlow, PyTorch, MXNet etc)
- Research experience in one or more of the following areas: large language models (LLMs), natural language understanding/processing, speech processing, dialog understanding, text summarization, question answering, time series analysis, event sequence analysis, or information retrieval
- Experience with Big Data technologies such as AWS, Hadoop, Spark, Hive, Lucene/SOLR, or Kafka
- Excellent command of at least one modern programming language (preferably Python)
- Strong publication record in top-tier ML and NLP conferences (e.g. ACL, NAACL, EMNLP, NeurIPS, ICML, AAAI, ICLR, SIGIR etc)
Responsibilities
- Drive adoption of scientific and engineering best practices for the entire model life cycle management (MLCM)
- Develop science and engineering roadmaps, run sprints, and drive quarterly/annual planning exercises
- Collaborate with Product Management, Program Management, UX Design, engineering, and other stakeholder teams to collect requirements, describe features, build technical designs, and execution strategies
- Hire and develop scientists at various experience levels by providing technical and career development guidance
- Drive operational perfection by investigating production issues, driving root cause analysis, and follow-up actions for continuous improvement
- Communicate research findings to a technical audience and executive management
- Represent Qualtrics in academic and industrial conferences
Other
- Ph.D. degree with 4+ years of applied research experience or a Master's degree and 6+ years of applied research experience
- 2+ years of people management experience
- Proven ability to hire, develop and manage high-performing applied science teams
- Comfortable with dealing with multiple priorities and ambiguity in a fast-paced, dynamic environment
- Excellent oral and written communication skills, with the ability to communicate complex technical concepts and solutions to both technical and non-technical teams at all levels of the organization
