Applied Scientist II

Qualtrics•Reston, VA

2d•Hybrid

About The Position

At Qualtrics, we create software the world’s best brands use to deliver exceptional frontline experiences, build high-performing teams, and design products people love. But we are more than a platform—we are the creators and stewards of the Experience Management category serving over 18K clients globally. Building a category takes grit, determination, and a disdain for convention—but most of all it requires close-knit, high-functioning teams with an unwavering dedication to serving our customers. When you join one of our teams, you’ll be part of a nimble group that’s empowered to set aggressive goals and move fast to achieve them. Strategic risks are encouraged and complex problems are solved together, by passing the mic and iterating until the best solution comes to light. You won’t have to look to find growth opportunities—ready or not, they’ll find you. From retail to government to healthcare, we’re on a mission to bring humanity, connection, and empathy back to business. Join over 5,000 people across the globe who think that’s work worth doing. Applied Scientist II Why We Have This Role We are looking for talented and innovative Applied Scientist 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 Machine Learning Applied Scientist at Qualtrics, you should love building cutting-edge predictive 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! How You’ll Find Success Leverage your deep knowledge of artificial intelligence (AI) principles, including machine learning, natural language processing, computer vision, and reinforcement learning. Use your understanding of both supervised and unsupervised learning techniques, and their applications in building intelligent systems. Develop and optimize algorithms for building scalable and efficient GenAI applications. Tackle challenging problems in creative ways, leveraging generative models to address real-world use cases and drive innovation. Use effective communication skills to articulate technical concepts to non-technical stakeholders and gather requirements for GenAI application development. Show strong programming skills in languages like Python, along with proficiency in deep learning frameworks such as TensorFlow, PyTorch, or similar. How You’ll Grow Passion for leveraging cutting-edge AI technology to create innovative GenAI applications that have a meaningful impact on businesses, industries, and society. Commitment to developing GenAI applications that adhere to ethical standards and promote positive societal impact while minimizing potential risks. Drive to push the boundaries of what's possible with AI, and to contribute to the advancement of the field through research, experimentation, and collaboration. Willingness to stay updated with the latest advancements in AI research and technology, and to continuously learn and adapt to new methodologies and best practices. Agility to pivot and iterate on GenAI applications based on feedback, emerging trends, and changing business requirements.

Requirements

Bachelors and Graduate Degrees 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.
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.

Nice To Haves

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.)

Responsibilities

Address challenges in products through Large Language Models, Deep Learning and Data Science approaches and publish research papers.
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
Contribute to and inspire the Conversational AI, NLP, and Data Science technology roadmap at Qualtrics.

Benefits

$1800 Experience bonus to be used for an “Experience” of your choosing
QMentorship Program matches you with a mentor inside Qualtrics to get meaningful coaching from someone outside your team.
Amazing QGroup Communities; MOSAIQ, Green Team, Qualtrics Pride, Q&Able, Qualtrics Salute, and Women’s Leadership Development, which exist as places for support, allyship, and advocacy.
The Qualtrics Hybrid Work Model: Our hybrid work model is elegantly simple: we all gather in the office three days a week; Mondays and Thursdays, plus one day selected by your organizational leader. These purposeful in-person days in thoughtfully designed offices help us do our best work and harness the power of collaboration and innovation. For the rest of the week, work where you want, owning the integration of work and life. #hybrid

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