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 Challenge

The mission of the coreML 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 currently looking for a talented and innovative applied science leader to bring our Machine Learning and Artificial Intelligence R&D capabilities to the next level.

The Role

As an Applied Science Manager (ASM), you will identify research directions, build translational research programs and communicate them to senior leadership, and work closely with other stakeholders to bring research to production. You will work with a talented team of applied scientists and machine learning engineers covering a broad spectrum of modeling needs for AI products. Some of our key challenges include the development of multilingual information extraction and retrieval systems, dialogue understanding, forecasting, model compression, schematization, anomaly detection, etc. This role will involve a high degree of ambiguity and multidisciplinary collaboration.

A Day in the Life

• Drive adoption of scientific and engineering best practices for the entire model life cycle management (MLCM), including research, model design, experiment design, model testing, coding standards/reviews, model monitoring, and launch processes
• 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

Basic Qualifications

• Ph.D. degree with 4+ years of applied research experience or a Master's degree and 6+ years of applied research experience
• Proven ability to hire, develop and manage high-performing applied science teams 
• Track record of conducting independent research and model development, implementation, and optimization to drive eventual product outcomes
• Solid understanding of machine learning fundamentals and tool ecosystem with deep and demonstrable expertise in at least one topic or application of machine learning.
• Solid understanding of elements of machine learning life cycle management.
• Familiarity with relevant technology stacks such as deep learning frameworks (TensorFlow, PyTorch, etc) and ML platforms such as SageMaker, VertexAI etc
• Comfortable with dealing with multiple priorities and ambiguity in a fast-paced, dynamic environment
• Excellent command of at least one modern programming language (preferably Python)
• 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

Preferred Qualifications

• Experience with defining and executing organizational research and development practices in an industry setting
• 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 natural language understanding/processing, speech processing, dialog understanding, text summarisation, question answering, knowledge graphs, time series analysis, event sequence analysis, information retrieval
• Strong publication record in top-tier ML and NLP conferences (e.g. ACL, NAACL, EMNLP, NeurIPS, ICML, AAAI, ICLR, SIGIR etc.)
• Experience with Big Data technologies such as AWS, Hadoop, Spark, Hive, Lucene/SOLR, or Kafka

The base pay range for this position in the US is $192.0k - $342.5k 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.