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Our mission is to help organizations serve and support customers and employees in proactive, personalized ways.
The Role
Develop and productionize machine learning models and scalable ML services for Qualtrics products. Build robust data pipelines for complex, multimodal data; design highly available microservices; optimize algorithms and systems; participate in architecture and design reviews; prototype solutions; collaborate with product and engineering teams; and mentor junior engineers. The role requires strong computer science fundamentals, applied ML experience, and proficiency in Python, Java, C#, TensorFlow, or PyTorch.
Summary Generated by Built In
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.
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.
Senior Machine Learning Engineer
Why We Have This Role
We are looking for an engineer to bring our Machine Learning and Artificial Intelligence R&D 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. You should love building simple solutions to solve hard customer problems. Crafting systems 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
- Work in a supportive environment enables individual growth and achievement of team goals
- Collaborate with your peers, prioritize features, and work with a sense of urgency to deliver value to our customers
- Develop scalable, robust, and highly available micro services to perform simple to complex statistical analyses and build/deploy machine learning models
- Implement new features and optimize existing ones to delight our customers
- Balance technical excellence with pragmatic decision-making to solve complex algorithmic challenges efficiently
How You’ll Grow
- Work in a multi-disciplinary team to implement, tune, and productize cutting-edge machine learning models to meet the demands of our rapidly growing business
- Build and maintain highly scalable data pipelines to cleanse, anonymize, measure, and index complex and multi-modal data.
- Take on mentorship roles and collaborative projects to refine your leadership skills and guide junior team members.
Things You’ll Do
- Work closely with, and incorporate feedback from other specialists, tech-ops, and product managers
- Lead and engage in design reviews, architectural discussions, requirement definitions and other technical activities in diverse capacity
- Attend daily stand-up meetings, collaborate with your peers, prioritize features, and work with a sense of urgency to deliver value to your customers
- Finding quick ways to prototype and test possible solutions to large problems
- Stay up-to-date with industry trends and academic research to evaluate new tools, frameworks, and modeling techniques.
What We’re Looking For On Your Resume
- Bachelor’s degree in Computer Science or related fields.
- 5-8 years of experience as a Machine Learning Engineer, demonstrating a strong track record in designing, implementing, and optimizing machine learning models for real-world applications, leveraging frameworks such as TensorFlow or PyTorch.
- Strong Computer Science fundamentals in algorithm design, complexity analysis, and performance
- Experience in programming with at least one modern programming language such as Java, C# or Python, including object-oriented design
- Experience with applied machine learning models and large-scale ML systems
- Excellent problem-solving and analytical skills, with the ability to break down complex problems into actionable components.
- Strong communication and collaboration skills, with the ability to work effectively within cross-functional teams.
What You Should Know About This Team
- The Data Intelligence Center of Excellence (DICE) organization provides AI/ML research and development services for all product lines. This team builds core machine learning infrastructure and services.
- The team's goal is to accelerate Qualtrics's ML adoption by enabling every engineering team to experiment, design, build, monitor, and troubleshoot ML-powered applications with a Platform that applies reusable components, patterns, and standards/best practices.
- Through close collaboration with product and engineering teams, we seamlessly integrate advanced intelligence into everyday user experiences.
Our Team’s Favorite Perks and Benefits
- Wellness Reimbursement for $300 per quarter for wellness activities including gym memberships, spa massages, workout equipment, meditation apps, and much more.
- Unlimited Sick Days
- 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
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, and mental health benefits. For a detailed look at our benefits, visit Qualtrics US Benefits.
Washington State Base Annual Pay Transparency Range
$177,500—$216,000 USD
Skills Required
- Bachelor's degree in Computer Science or a related field
- 5-8 years of experience as a Machine Learning Engineer
- Experience designing, implementing, and optimizing machine learning models for real-world applications
- Experience with TensorFlow or PyTorch
- Strong computer science fundamentals in algorithm design, complexity analysis, and performance
- Programming experience in at least one modern language such as Java, C#, or Python
- Object-oriented design experience
- Experience with applied machine learning models and large-scale ML systems
- Excellent problem-solving and analytical skills
- Strong communication and collaboration skills
What the Team is Saying
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Software Engineer
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The Company
What We Do
Qualtrics is trusted by thousands of the world’s best organizations to power exceptional customer and employee experiences that build deep human connections, increase customer loyalty, boost employee engagement, and drive business success. Our advanced AI and specialized Experience Agents™ allow businesses and governments to proactively interact with customers and employees in personalized ways across every channel and touchpoint, respond in-the-moment to fix or improve experiences, and stay across the latest market trends and opportunities. Our vision, as an organization, is to improve the human experience.
Why Work With Us
We're a place where strategic risks are encouraged & complex problems get solved together. Where nimble teams are empowered to set aggressive goals & move fast to win. A place that makes you feel safe as your authentic self. Where everyday work results in growth. And, most importantly, where what you do matters. That's why we work at Qualtrics.
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About our Teams
Qualtrics Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
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.
Typical time on-site:
3 days a week
