Data Engineering
ML Engineering
You architect systems that turn raw data into intelligent decisions at enterprise scale. This path breeds technical leaders who speak both machine learning and business strategy fluently.
Career Progression
Rotational Tours · L1–L3
Build the craft. Prove you can wield the tools of Data Engineering.
Transformational Tours · L4–L7
Deliver outcomes. Each tour has a defined mission and success criteria.
Foundational Tours · L8–L10
Shape the organization. Build institutions, not just products.
What Hiring Managers Look For
You ship production ML models that move business metrics, not just experiments in notebooks.
You architect systems that scale beyond the data science team's laptop—distributed training, model serving infrastructure, and MLOps pipelines that survive production chaos.
You transform how the organization thinks about data products, building platforms that democratize ML capabilities across business units while maintaining governance and reliability standards.
Common Career Transitions
ML Engineering → Platform Engineering at L5-L6 for broader infrastructure ownership beyond ML workloads
ML Engineering → Product Data Science at L4-L5 to drive business strategy through advanced analytics