Machine Learning Engineer
Why WWT?
At World Wide Technology, we work together to make a new world happen. Our important work benefits our clients and partners as much as it does our people and communities across the globe. WWT is dedicated to achieving its mission of creating a profitable growth company that is also a Great Place to Work for All. We achieve this through our world-class culture, generous benefits and by delivering cutting-edge technology solutions for our clients.
WWT was founded in 1990 in St. Louis, Missouri. We employ more than 10,000 people globally and closed nearly $20 billion in revenue in 2023. We have an inclusive culture and believe our core values are the key to company and employee success. WWT is proud to have been included on the FORTUNE "100 Best Places to Work For®" list 12 years in a row!
Want to work with highly motivated individuals on high-performance teams? Join WWT today!
What is the Solutions Consulting & Engineering (SC&E) Team and why join?
Solutions Consulting & Engineering is an organization that is Customer Focused and Solutions Led. We deliver end-to-end (E2E) and emerging solutions to drive customer satisfaction, increase profitability and growth. Our success is enabled by our world-class management consulting, delivery excellence and engineering brilliance. We embody the OneWWT mindset by bringing the right talent at the right time from anywhere within WWT to solve our customer's problems. Our goal is to bring together business acumen with full-stack technical know-how to develop innovative solutions for our clients' most complex challenges.
RESPONSIBILITIES:
Develop, productionize, and deploy scalable, resilient software solutions to integrate and operationalize AI & ML capabilities. Adhere to software architecture and software design best practices to write scalable, maintainable, well-designed code. Develop automated end-to-end ML delivery pipelines; enabling model training, evaluation, tracking, and serving. In collaboration with Data Engineering, design and build feature engineering pipelines for extraction, transformation, and loading of data from a variety of data sources for ML models. Advocate for AI security and responsibility best practices. Enable monitoring and observability capabilities for the delivery teams. Stay current on new developments in ML frameworks, tooling, data modelling, software architecture and libraries available for solution development. Coach data scientists and data engineers on software development best practices. Agile Project Work
Work in cross-functional agile teams of highly skilled software/machine learning engineers, data scientists, DevOps engineers, designers, product managers, technical delivery teams, and others to continuously innovate AI and MLOps solutions Act as a positive champion for broader organization to develop stronger understanding of software design patterns that deliver scalable, maintainable, well-designed analytics solutions Acts as an expert on complex technical topics that require cross-functional consultation