Senior Machine Learning Engineer

Qualtrics•Seattle, WA

3h•$177,500 - $216,000•Hybrid

About The Position

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. As a Senior Machine Learning Engineer, you will be responsible for bringing our Machine Learning and Artificial Intelligence R&D strategy to the next level. You will work within the Data Intelligence Center of Excellence (DICE) organization to build core machine learning infrastructure and services, aiming to personalize the Qualtrics experience. The role involves developing scalable, robust, and highly available microservices to perform statistical analyses and deploy machine learning models in an agile, fast-paced environment.

Requirements

Bachelor’s degree in Computer Science or related fields
5-8 years of experience as a Machine Learning Engineer
Strong track record in designing, implementing, and optimizing machine learning models for real-world applications
Experience with 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
Strong communication and collaboration skills

Responsibilities

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
Balance technical excellence with pragmatic decision-making
Work in a multi-disciplinary team to implement, tune, and productize cutting-edge machine learning models
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
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
Attend daily stand-up meetings
Find quick ways to prototype and test possible solutions
Stay up-to-date with industry trends and academic research