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Staff Machine Learning Engineer - DICE

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.

 

Staff Machine Learning Engineer

 

Why We Have This Role

We are looking for an experienced Machine Learning 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. We aim to enhance our capabilities in developing and maintaining high-performance systems that can effectively handle large volumes of data and complex algorithms. This role will be pivotal in driving innovation and ensuring our machine learning initiatives support our mission of closing experience gaps across various domains.

 

How You’ll Find Success

  • Working in a supportive environment enables individual growth and the achievement of team goals.
  • Collaborate with your peers, prioritize features, and work with a sense of urgency to deliver value to our customers.
  • It will be crucial to stay on top of technology trends and educate leadership and stakeholders on trends, and North Star initiatives.
  • Analyze and enhance ML systems for better performance and efficiency.
  • Develop creative solutions to improve our ML infrastructure and scalability

 

How You'll Grow

  • Expand your expertise in machine learning and software engineering by working on cutting-edge technologies and large-scale systems.
  • Take on mentorship roles and collaborative projects to refine your leadership skills and guide junior team members.
  • Gain insights into different areas of the business by collaborating with various teams, enriching your understanding of how technology impacts overall company strategy.

 

Things You’ll Do

  • Design and develop robust AI architectures, frameworks, and algorithms that can support large-scale and complex enterprise SaaS AI solutions in alignment with business objectives. 
  • Evaluate and select appropriate AI technologies, tools, and frameworks to achieve desired performance, accuracy, and scalability.
  • Collaborate across the company to guide the direction of machine learning at Qualtrics, spanning teams from research to production.
  • Communicate with a team of research scientists, product managers, and engineers and lead and document AI architectures, design decisions, and technical specifications for reference and knowledge sharing.
  • Work closely with research scientists and model engineering teams on developing, and deploying, ML systems in production. Develop a strategy for optimizing models and systems for performance, scalability, efficiency, and cost.
  • Offer technical supervision and direction to the ML platform teams and lead the creation of future ML platform for deploying and monitoring AI models in production settings while maintaining compliance with the best practices in machine learning and deep learning.
  • Conduct regular code reviews and provide technical guidance to team members.
  • Stay up-to-date with the latest advancements in AI technologies, frameworks, and algorithms, and identify opportunities for their application in the organization.

 

What We’re Looking For On Your Resume

  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.
  • Proven experience (7+ years) working as a Machine Learning Engineer, or related role.
  • Proficiency in programming languages such as Python, Java, or C++, and popular AI libraries and frameworks (e.g. TensorFlow, PyTorch, Keras).
  • Solid understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models on these platforms.
  • 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.
  • Ability to stay updated with the latest AI technologies, frameworks, and platform advancements.
  • Knowledge of deploying and optimizing LLMS with open-source frameworks like DeepSpeed, Accelerate, FasterTransformer, and Transformers-NeuronX libraries is a plus.
  • Knowledge of ethical considerations and responsible AI practices is a plus.

 

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 role will specifically be on the Data Intelligence Platform (DIP) team which works on building services and tools that enable ML and intelligence across multiple products. 
  • The DIP 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.

 

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.
  • $1800 yearly Experience bonus to be used for an “Experience” of your choosing
  • 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.
 
Not finding a role that’s the right fit for now? Qualtrics Insiders is the one-stop shop for all things Qualtrics Life. Sign up for exclusive access to content created with you in mind and get the scoop on what we have going on at Qualtrics - upcoming events, behind the scenes stories from the team, interview tips, hot jobs, and more. No spam - we promise! You'll hear from us two times a month max with fresh, totally tailored info - so be sure to stay connected as you explore your best role and company fit.

 

For full-time positions, this pay range is for base per year; however, base pay offered 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, in addition to a range of medical, financial, and other benefits, based on eligibility criteria.

Washington State Annual Pay Transparency Range
$195,000$355,500 USD

Average salary estimate

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$195000K
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What You Should Know About Staff Machine Learning Engineer - DICE, Qualtrics

Are you ready to take your career to the next level? Join Qualtrics as a Staff Machine Learning Engineer and be a crucial part of a team that’s revolutionizing the way brands connect with their customers. Located in the vibrant city of Seattle, Washington, this role is designed for those who are passionate about Machine Learning and AI, eager to work in a dynamic environment where collaboration is key. At Qualtrics, we pride ourselves on our innovative spirit and commitment to delivering software that enhances frontline experiences, helping organizations of all sizes—from retail to healthcare—achieve their goals. As a Staff Machine Learning Engineer, you’ll drive our ML and AI research and development strategy forward. Your work will help personalize how our clients leverage Qualtrics data, transforming their operations with cutting-edge solutions. You'll design and develop robust AI architectures and collaborate with talented research scientists and engineers to optimize systems for performance, scalability, and efficiency. With ample growth opportunities at your fingertips, you’ll not only enhance your technical skills but also take on mentorship roles that lift the entire team. If you’re looking to make a tangible impact and grow within a culture that values ingenuity and teamwork, this is the role for you!

Frequently Asked Questions (FAQs) for Staff Machine Learning Engineer - DICE Role at Qualtrics
What are the main responsibilities of a Staff Machine Learning Engineer at Qualtrics?

As a Staff Machine Learning Engineer at Qualtrics, your responsibilities include designing and developing robust AI architectures and algorithms that align with business objectives. You'll evaluate and select appropriate AI tools and frameworks, collaborate with cross-functional teams, and lead initiatives that enhance the machine learning experience across multiple products. Additionally, you'll work closely with research scientists, conduct code reviews, and stay updated with advancements in AI technologies.

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What qualifications do I need to become a Staff Machine Learning Engineer at Qualtrics?

To qualify for the Staff Machine Learning Engineer position at Qualtrics, candidates should possess a Bachelor’s or Master’s degree in Computer Science, AI, or a related field. You'll need at least 7 years of relevant experience in similar roles, proficiency in programming languages like Python or Java, and a strong understanding of cloud computing platforms. Furthermore, familiarity with AI libraries and ethical AI practices is advantageous.

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What does the team culture look like for Staff Machine Learning Engineers at Qualtrics?

The culture for Staff Machine Learning Engineers at Qualtrics is highly collaborative and supportive. The Data Intelligence Center of Excellence (DICE) fosters an environment where experimentation and innovation are encouraged, allowing team members to push the boundaries of what's possible in machine learning and AI. You'll find that mentorship and knowledge-sharing are key aspects of the team dynamic, contributing to both personal and team growth.

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How does a Staff Machine Learning Engineer contribute to Qualtrics's mission?

As a Staff Machine Learning Engineer at Qualtrics, you play a pivotal role in closing experience gaps across various domains by developing machine learning solutions that improve customer engagement and operational efficiency. By leveraging advanced AI technologies, you help ensure that Qualtrics remains a market leader in Experience Management by personalizing solutions that meet diverse client needs.

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What opportunities for growth can a Staff Machine Learning Engineer expect at Qualtrics?

At Qualtrics, Staff Machine Learning Engineers can expect numerous growth opportunities, including enhancing their expertise through collaboration on cutting-edge technologies and large-scale systems. You’ll also have chances to take on mentorship roles, participate in impactful projects, and gain insights into how technology aligns with overall business strategy, thereby refining your leadership and technical skills.

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Common Interview Questions for Staff Machine Learning Engineer - DICE
What experience do you have with machine learning algorithms?

When preparing to answer this question, highlight specific algorithms you have experience with, such as decision trees, neural networks, or support vector machines. Discuss projects where you successfully implemented these algorithms, detailing the challenges faced and how you overcame them to achieve positive outcomes.

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Describe a situation where you had to optimize a machine learning model.

In responding to this question, provide a clear example where you identified an underperforming model. Discuss the strategies you employed for optimization, such as feature engineering, parameter tuning, or changing the algorithm, and quantify the improvements made to the model's performance.

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How do you stay current with developments in machine learning technology?

Emphasize your strategies for keeping up-to-date with the rapidly evolving field of machine learning. Mention resources such as online courses, research papers, tech conferences, and communities that you engage with regularly to enhance your knowledge and skills.

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What are the key considerations when deploying machine learning models in production?

Answer this question by discussing crucial topics such as scalability, performance monitoring, data privacy, and compliance. Explain the importance of testing and validation before deployment and your familiarity with CI/CD pipelines in machine learning environments.

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Can you explain a complex technical concept to someone with non-technical background?

Use this opportunity to showcase your communication skills. Choose a concept related to machine learning, such as overfitting or model accuracy, and break it down using simple, relatable analogies. This demonstrates your ability to convey complex information clearly and effectively.

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Have you ever dealt with a significant data issue? How did you handle it?

Highlight a specific instance where you tackled a data-related challenge, such as missing values or data bias. Explain your approach to resolving the issue, the techniques you employed, and the end result of your intervention.

Join Rise to see the full answer
Describe your experience with cloud computing platforms.

Prepare to discuss specific cloud platforms you have worked with (e.g., AWS, Azure) and how you used them to deploy machine learning models. Provide examples demonstrating your confidence in leveraging cloud resources for scalability and efficiency.

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What ethical considerations do you think are important in machine learning?

Discuss the significance of bias, fairness, and transparency in machine learning. Share your understanding of responsible AI practices and how you incorporate them into your work to mitigate ethical concerns in model development and deployment.

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Tell me about a time when you led a project or a team.

This is your chance to highlight your leadership skills. Detail a project you led, focusing on your role in guiding the team, the strategies you implemented for team collaboration, and how your leadership contributed to the project's success.

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What tools and frameworks do you prefer to use in your machine learning projects?

List the tools and frameworks you are most proficient with, such as TensorFlow or PyTorch, and explain why you favor them. Discuss how these tools have helped facilitate your work in past projects, highlighting any specific successes they contributed to.

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At Qualtrics, our mission is to build technology that closes experience gaps.

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DATE POSTED
April 7, 2025

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