Staff Machine Learning Engineer

Qualtrics • Seattle, WA

2d • Hybrid

About The Position

Qualtrics is seeking an experienced Machine Learning Engineer to advance its machine learning and artificial intelligence research and development strategy. The role focuses on personalizing the Qualtrics experience through ML and AI features, using Qualtrics data as a core value proposition, and building high-performance systems capable of handling large volumes of data and complex algorithms. The position is on the Data Intelligence Platform (DIP) team within the Data Intelligence Center of Excellence (DICE), which develops services and tools that enable machine learning and intelligence across multiple product lines. The team aims to accelerate ML adoption by giving engineering teams reusable components, patterns, standards, and best practices for experimenting, building, monitoring, and troubleshooting ML-powered applications.

The Staff Machine Learning Engineer will design and develop AI architectures, frameworks, and algorithms for large-scale enterprise SaaS solutions. The role collaborates with research scientists, product managers, engineers, and ML platform teams to guide machine learning direction from research through production. It also includes setting strategies for model and system optimization, providing technical supervision and guidance, documenting architecture and design decisions, conducting code reviews, and staying current with AI advancements.

The position follows Qualtrics’ hybrid work model: employees work in the office three days each week—Mondays, Thursdays, and one day selected by their organizational leader—and may work from wherever they choose for the rest of the week. The listed Washington State base annual pay range is $213,000–$259,000. A sign-on bonus and restricted stock units may be included in an employment offer.

Requirements

• Bachelor’s or master’s degree in Computer Science, Artificial Intelligence, or a related field.
• At least 7 years of experience working as a Machine Learning Engineer or in a related role.
• Proficiency in programming languages such as Python, Java, or C++.
• Experience with AI libraries and frameworks such as TensorFlow, PyTorch, or Keras.
• Solid understanding of cloud computing platforms such as AWS, Azure, or Google Cloud.
• Experience deploying AI models on cloud platforms.
• Strong problem-solving and analytical skills, including the ability to break complex problems into actionable components.
• Strong communication and collaboration skills and ability to work effectively in cross-functional teams.
• Ability to stay updated on AI technologies, frameworks, and platform advancements.

Nice To Haves

• Knowledge of deploying and optimizing large language models with open-source frameworks such as DeepSpeed, Accelerate, FasterTransformer, and Transformers-NeuronX libraries.
• Knowledge of ethical considerations and responsible AI practices.

Responsibilities

• Design and develop robust AI architectures, frameworks, and algorithms for large-scale, complex enterprise SaaS AI solutions, aligned with business objectives.
• Evaluate and select 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, across research and production teams.
• Communicate with research scientists, product managers, and engineers; lead and document AI architectures, design decisions, and technical specifications.
• Work with research scientists and model engineering teams to develop and deploy ML systems in production.
• Develop strategies for optimizing models and systems for performance, scalability, efficiency, and cost.
• Provide technical supervision and direction to ML platform teams and lead the creation of a future ML platform for deploying and monitoring AI models in production.
• Maintain compliance with machine learning and deep learning best practices.
• Conduct code reviews and provide technical guidance to team members.
• Stay current with AI technologies, frameworks, and algorithms and identify opportunities to apply them.
• Analyze and improve ML systems for performance and efficiency.
• Develop solutions to improve ML infrastructure and scalability.
• Collaborate with peers, prioritize features, and deliver customer value.
• Educate leadership and stakeholders about technology trends and North Star initiatives.

Benefits

• $300 per quarter wellness reimbursement for activities such as gym memberships, spa massages, workout equipment, and meditation apps.
• QGroup communities for support, allyship, and advocacy.
• Medical, dental, vision, life, and disability benefits for full-time employees.
• 401(k) with match.
• Paid time off.
• Mental health benefits.
• A sign-on bonus and restricted stock units may be included in an employment offer.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior