Principal Machine Learning Engineer
Why Qualtrics:
Qualtrics is the technology platform that organizations use to collect, analyze, and act on experience data, also called X-data™. The Qualtrics XM Platform™ is a system of action, used by teams, departments, and entire organizations to manage the four core experiences of business—customer, product, employee and brand—on one platform. Over 10,000 enterprises worldwide, including more than 75 percent of the Fortune 100 and 99 of the top 100 U.S. business schools, rely on Qualtrics to consistently build products that people love, create more loyal customers, develop a phenomenal employee culture, and build iconic brands. Qualtrics was recently acquired by SAP, and together we will accelerate XM globally and power the experience economy. Join us on this adventure and define the future of Experience Management from technical perspective! If you’re searching for a company that’s dedicated to your ideas and growth, recognizes your unique contribution, fills you with purpose, and provides a fun, flexible and inclusive work environment - apply now!
The Challenge:
Our goal is to personalize the Qualtrics experience using ML and AI features showcasing Qualtrics data as a core value proposition and competitive advantage.
As a Machine Learning software engineer at Qualtrics, 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!
Expectations for Success:
- A passion for building simple solutions to solve complex customer problems.
- Craft systems in an agile environment to withstand hyper growth and owning quality from end to end
- Effectively research and benchmark Qualtrics’ technology against other best-in-class technologies and participate in technology adoption decisions.
- Work with Research Engineers to implement, tune, and productize machine learning models
- Develop new algorithms with a track record in top journals or conferences
- Conduct state-of-the-art research, system design, and apply novel techniques to live production systems
- Develop scalable, fast, robust, and simple web-based solutions to solve complex business problems
- Implement new features and optimize existing ones to drive maximum performance
- Attend daily stand-up meetings, collaborate with your peers, prioritize features, and work with a sense of urgency to deliver value to your customers
Requirements
- Minimum of a Bachelor's of Science degree in Computer Science or related field
- 12+ years of relevant, broad engineering experience
- Deep expertise with Machine Learning systems over the entire software development lifecycle:
- Designing for scale, quality, and stability, especially with an eye to machine learning models in NLP, computer vision, statistical analysis, data mining, etc.
- Experience in software engineering standard methodologies (e.g. code versioning, unit testing, code reviews, design documents, and data modeling)
- Maintenance and enhancements once in production
- Experience with one or more deep learning frameworks: e.g Tensorflow, PyTorch, MXNet
- Experience with large-scale computing platforms, e.g Spark, Hadoop
- Consistent track record of leading the delivery of large-scale, high-quality SaaS systems
A Day in the Life:
- You'll create end-to-end Machine Learning systems - consistent model training, evaluation, deployment and delivery for batch, streaming and real time use.
- You'll work collaboratively with Engineers, Applied Scientists and cross functional teams in crafting and implementing AI Platform's technical vision.
- You will balance significant long-term R&D investments with short-term product deliverables, and partner with product management and company leadership to ensure alignment against strategic and tactical goals.