General Motors - Indianapolis, IN
posted about 2 months ago
The Staff ML Engineer will be responsible for driving the vision and execution of LiftIQ, a Marketing Experimentation and Optimization Platform. This individual will serve as a technical leader with expertise in building scalable Machine Learning data products for experimentation and optimization. This includes experiment design, statistical and ML models for measurement, optimization, and personalization, leveraging both first-party and third-party data sources. The role requires collaboration with cross-functional teams, including engineering, data science, and UX/UI design, to build and refine the platform that enables experimentation, measurement, and optimization. In this position, the Staff ML Engineer will work closely with stakeholders in GM's vehicle brands, subscriptions, and customer care products, as well as the Performance Driven Marketing team. The goal is to ensure business acceptance of models, metrics, and visualization of experiment performance and optimization. The engineer will be responsible for developing platforms, tools, and democratized capabilities that allow stakeholders and data scientists to identify marketing initiatives with high return on investment. The team is focused on delivering future-focused, consumer-centric, personalized solutions that allow GM to stay proactive and nimble in the transition to electric vehicles (EVs). The Staff ML Engineer will work closely with Data Scientists, Engineers, and Product Owners to build a system that helps marketing stakeholders optimize ROI. They will design and engineer efficient and resilient ML platforms and software products that run at scale. Participation in design, architecture, and code reviews is expected, fostering collaboration and guiding the team through roadmap deliverables and technical challenges. The engineer will raise the bar of ML engineering by improving best practices, producing exemplary code, documentation, automated tests, and thorough monitoring. Possessing contextual business knowledge and functional domain expertise in experimentation systems related to marketing, media, customer, digital channels, loyalty, and subscription space is crucial to drive incremental value. The engineer will drive a strategic roadmap with executable outcomes to provide business value and impact, while also managing strong stakeholder relationships to prioritize requests and move them from curiosity to realized data products, insights, and solutions. Additionally, they will lead and develop a team capable of tackling diverse problems across the business, ensuring high delivery quality through the creation of internal structures and extensible frameworks to manage accountability and develop staff.