Manager, Machine Learning

Seattle, Washington, United States

Job Description

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.

Machine Learning Engineering Manager - AI Core

Why We Have This Role

The AI Core organization at Qualtrics manages the entire model development lifecycle for AI/ML and Agentic applications. It consists of ML engineers, applied scientists, and data and infrastructure engineers who provide the platforms, frameworks, tools, and services needed for safe, scalable, and accessible AI/ML development and deployment. The platform engineering team builds an enterprise-grade AI/ML system compliant with security and industry standards such as FedRAMP, ISO42001, GDPR, HIPAA, and PCI. Within this platform, you will lead a team responsible for the architecture, development, and operation of core reusable AI/ML components, including training pipelines, online model serving, feature stores, voice transcription, event stream processing, and LLM serving. This team handles services that process billions of requests weekly across Qualtrics. You will also lead projects and collaborate with ML practitioners and senior engineers to shape the future of Qualtrics' AI and model serving infrastructure, reporting to the Director of AI Core’s Platform Engineering team.

How You’ll Find Success

Connect Strategy to Execution: Translate organizational priorities into a clear, actionable technical vision and long-term roadmap for the AI Core Platform, aligning work with the broader mission.
Drive Technical Excellence: Build a scalable, highly-available, and cost-efficient ML platform services to deliver delightful user experiences and ensure community safety.
Innovation & Adoption: Direct the evaluation and integration of new ML frameworks, including LLMs, Generative AI, and agentic solutions, keeping Qualtrics at the forefront of Experience Management (XM) AI.
Build strong, trust-based relationships across Product, Data Infrastructure, and ML/Applied Science teams. Drive technical consensus and coordinate execution for large, cross-cutting platform initiatives and roadmap for our AI platform.
Instill an MLOps culture, standardizing best practices in feature engineering, model observability, governance, and infrastructure.

How You’ll Grow

Context Mastered and Team Embedded: You quickly develop a deep understanding of the team's structure, systems, workflows, and cultural norms, building the situational awareness needed to lead with clarity and effectiveness.
High-Performing Team Building: Own and evolve the engineering hiring process, focusing on quality, equity, and candidate experience.
Lead, mentor, and grow high-performing Machine Learning Engineers, providing clear career paths, constructive feedback, and growth opportunities.

Things You’ll Do

Define and gain alignment on a multi-quarter technical roadmap for one or more critical platform areas (e.g., LLM Serving or the Feature Store), demonstrating a clear plan for scalable, measurable impact.
Run Team Operations with Structure and Empathy: Lead execution through consistent team rituals (planning, retrospectives, one-on-ones), balancing structure with empathy for alignment and psychological safety.
Stay hands-on by participating in code reviews, technical design discussions, and occasionally contributing to the codebase.
Instill best practices for software development and documentation, ensuring high-quality deliverables on time.
Actively manage, mentor, and coach your team, fostering professional development and strong team culture.
Work closely with global clients to provide solutions and ensure outstanding customer experiences.
Recruit, hire, and develop top engineering talent to build a world-class team.

What We’re Looking For On Your Resume

10+ years of total experience in ML engineering, focusing on large-scale data, distributed systems, or ML infrastructure.
3+ years of direct people management, leading high-performing ML teams, building models for business application experience and development of senior/staff talent.
Proven ability to build and lead engineering teams with strong product ownership and end-to-end accountability.
Deep technical knowledge in building and operating AI/ML Platforms supporting the full model lifecycle, including orchestration.
Experience building and shipping enterprise-grade AI solutions for global customers.
Demonstrated success as an engineering manager, showing measurable outcomes like improved velocity, reduced cycle time, and scaling teams through high-growth AI apps.
Successful track record leading complex, cross-functional initiatives across distributed teams, aligning engineering execution with product/business goals.
Strong grasp of SRE and MLOps principles, expertise in system scalability, cloud cost optimization, AI observability, and production security.
Experience programming in Java, C++, Python or related language
Hands-on experience with real-time AI and Agentic services (e.g., Kubernetes, Sagemaker, Bedrock, Langgraph) and deploying GenAI applications, LLMs, or agent frameworks.
Bonus points:
- Experience establishing and managing cloud infrastructure budgets (e.g., AWS, GCP, Azure) by designing for efficiency and scale.
- Experience building or contributing to open-source tools within the ML ecosystem.
- Experience with FedRAMP, ISO 42001, GDPR, PCI, HIPAA and other standards.
- Advanced degree (M.S. or Ph.D.) in Computer Science, Data Science, or a related technical field.

What You Should Know About This Team

We are a group of talented and passionate engineers developing new products within the Qualtrics platform that enable Contact Center use cases. Our team, Care, was created to help contact centers scale their impact by assisting agents during calls and providing post-call analytics to improve the quality of care for customers. We focus on AI/ML-driven services and applications that enhance the overall customer experience.
Our engineers collaborate closely with platform teams to ensure our products are tightly integrated and consistent with core platform behavior. At the same time, we have the flexibility to choose our own architecture and the independence to quickly deliver on our business vision.
With broad product ownership and a true mandate for full-stack development, our team offers an amazing opportunity for career growth and building a strong foundational understanding across Qualtrics systems.

Our Team’s Favorite Perks and Benefits

We participate in personalized Career Action Planning. You will work with your manager to design a plan based on your life experiences, values, and career aspirations (inside and outside Qualtrics) that helps you achieve your career goals at Qualtrics
Full time employees receive an annual experience bonus after their first year of employment. Qualtrics Experience Bonus is a program designed to provide experiences to our employees they might not otherwise have.
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.

Qualtrics is an equal opportunity employer meaning that all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other protected characteristic.

Applicants in the United States of America have rights under Federal Employment Laws:Family & Medical Leave Act, Equal Opportunity Employment, Employee Polygraph Protection Act

Qualtrics is committed to the inclusion of all qualified individuals. As part of this commitment, Qualtrics will ensure that persons with disabilities are provided with reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please let your Qualtrics contact/recruiter know.

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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. A sign-on bonus and restricted stock units may be included in an employment offer. Full-time employees are eligible for medical, dental, vision, life and disability, 401(k) with match, paid time off, a wellness reimbursement, mental health benefits, and an experience bonus. For a detailed look at our benefits, visit Qualtrics US Benefits.

Washington State Annual Pay Transparency Range

$222,000—$319,000 USD

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