Staff Applied Scientist

About the role

Qualtrics is on the lookout for a Staff Applied Scientist to enhance our initiatives in artificial intelligence and machine learning. In this role, you will spearhead research and development projects aimed at embedding intelligent functionalities throughout our platform, significantly influencing how our diverse global clientele manages their experience data. You will own the end-to-end lifecycle of high-impact AI initiatives, translating ambiguous business challenges into robust technical solutions. This position requires you to act as a technical leader, driving innovation while ensuring that scientific rigor is applied to real-world product problems. You will define the architecture for scalable intelligent features that directly impact customer success and retention. Furthermore, you will mentor other researchers and engineers to elevate the overall technical bar of the organization. Your work will bridge the gap between cutting-edge academic research and production-grade software delivery. Ultimately, you will be responsible for ensuring that our AI capabilities remain at the forefront of the experience management industry.

Key facts

What you'll do

• Design and implement machine learning models that address the demands of a rapidly expanding business across multiple touchpoints.
• Lead design evaluations and modeling discussions to establish precise technical requirements for complex, multi-phase projects.
• Set benchmarks for experimentation, reproducibility, and monitoring in production environments while guiding junior scientists.
• Advocate for Evaluation-Driven Development by embedding automated testing and risk assessments throughout the agentic lifecycle.
• Architect and refine algorithms specifically tailored for scalable Generative AI applications that handle high-volume enterprise workloads.
• Disseminate research outcomes to the broader technical community and synthesize the latest advancements to inform product strategy.
• Partner with product managers and engineers to effectively integrate feedback into iterative model development processes.
• Drive cross-functional collaboration to ensure that technical capabilities align precisely with overarching business objectives.
• Analyze performance metrics using statistical methods to optimize existing models for enhanced efficiency and accuracy.
• Participate in strategic planning sessions to shape AI initiatives that directly support long-term company goals.
• Cultivate an innovative team culture by encouraging exploration of novel ideas and emerging technologies.
• Evaluate large language model tool-use reliability through systematic benchmarking within CI/CD pipelines.
• Maintain deep expertise in information retrieval systems to ensure accurate and context-aware AI responses.
• Oversee the deployment of models into scalable cloud environments with a focus on latency and reliability.

Requirements

• Hold a Bachelor's degree and a Ph.D. in Computer Science or a closely related discipline from an accredited institution.
• Possess a minimum of 7 years of practical research experience in machine learning, natural language processing (NLP), information retrieval, deep learning, or similar quantitative fields.
• Demonstrate strong proficiency in Python and hands-on familiarity with major deep learning frameworks such as PyTorch, TensorFlow, or MXNet.
• Have essential experience with machine learning platforms like SageMaker or MLFlow for managing the full model lifecycle.
• Show a proven ability to assess complex, multi-turn agentic systems with an emphasis on tool-use reliability and robust benchmarking.
• Integrate evaluation methodologies directly into CI/CD pipelines to ensure consistent model performance.
• Communicate technical concepts effectively to non-technical stakeholders through clear writing and structured presentations.
• Thrive in a fast-paced environment where priorities evolve rapidly and require immediate adaptation.
• Collaborate successfully within distributed teams across different time zones and cultural backgrounds.
• Commit to maintaining high standards of code quality, documentation, and experimental rigor.
• Apply analytical thinking to diagnose model failures and propose actionable improvements.
• Engage in continuous learning to keep up with rapid advancements in the field of artificial intelligence.
• Adhere to company policies and ethical guidelines regarding data privacy and responsible AI usage.
• Hold eligibility to work in the United States without sponsorship for this position.

Nice to have

• Build a record of publications in prestigious conferences such as NeurIPS, ICML, SIGIR, ICLR, ACL, or EMNLP to demonstrate thought leadership.

-拥有在生产环境中部署机器学习模型的实际经验 with high-traffic applications.

• Demonstrate familiarity with cloud computing platforms and their native integration with machine learning workflows.

-拥有使用基础设施即代码工具管理机器学习生命周期的经验.

-展示过优化模型以满足严格的 latency 和 throughput 要求的能力.

-拥有处理大规模数据集和使用分布式训练框架的实际经验.

-展示过对生成式 AI 系统的安全性和偏见问题的深入理解.

Skills & tools

• Expertise in Machine Learning, Natural Language Processing, Computer Vision, and Reinforcement Learning across diverse use cases.
• Knowledge of Generative AI evaluation frameworks used for testing large language models at scale.
• Proficiency in Python, TensorFlow, PyTorch, MXNet, SageMaker, and MLFlow for building and maintaining production pipelines.
• Experience with version control systems, containerization technologies, and orchestration platforms relevant to ML workflows.
• Understanding of data pipeline construction and ETL processes for training and inference workloads.

Practical notes

• The role follows a hybrid work model, requiring you to be in the office three days a week: Mondays, Thursdays, and one additional day as determined by leadership.
• Benefits offered include comprehensive medical, dental, and vision insurance, life and disability coverage, and a 401(k) plan with matching contributions.
• Employees receive a quarterly wellness reimbursement of $300 and an annual experience bonus of $1,800.
• You will have access to various internal QGroup communities, including MOSAIQ, Green Team, Qualtrics Pride, Q&Able, Qualtrics Salute, and Women's Leadership Development.
• Qualtrics is committed to being an equal opportunity employer, providing reasonable accommodations for the application and interview processes upon request.

Join us at Qualtrics, where your expertise will play a crucial role in shaping the future of experience management through innovative AI solutions. If you are about leveraging technology to create impactful experiences, we encourage you to apply and be part of our dynamic team.