Qualtrics

Applied Scientist II

Seattle, Washington, United States · Mid · Full-time

Sponsorship not specified$168k-$220kDetected 6 days ago

PythonAlgorithmsRESTMachine LearningDeep LearningTensorFlowPyTorchData ScienceNLPComputer VisionLLMsAgentic AIA/B TestingResearchLeadershipCommunicationCollaborationMentoring

About the role

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.
Join over 5,000 people across the globe who think that's work worth doing.

Responsibilities

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.
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.
Lead and engage in design reviews, modeling discussions, requirement definitions and other technical activities in diverse capacity
Design, build, and evaluate Agentic AI systems to solve complex customer challenges.

Requirements

Experience with Agentic AI systems, including design, development, and rigorous evaluation of agent performance.
We conduct ML modeling with deep expertise and rigor, including model selection, training, fine-tuning, customization, explainability, and evaluation.

Nice to have

Mondays and Thursdays, plus one day selected by your organizational leader.
Applicants in the

Compensation

For full-time positions, this pay range is for base per year; however, base pay offered within this range may vary depending on location, job-related knowledge, education, skills, and experience.

Benefits

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.
Show strong programming skills in languages like Python, along with proficiency in deep learning frameworks such as TensorFlow, PyTorch, or similar.
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
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)
Deep understanding of machine learning model life cycle management
Knowledge of or experience in building production quality and large scale deployment of applications related to machine learning
Experience in machine learning systems (e.g. SageMaker, MLFlow), and deep learning frameworks (e.g. TensorFlow, PyTorch, MXNet etc)

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