Storytelling is, and will always be, the heart of what we do at Skydance.
Our vision is to build a thriving entertainment ecosystem where stories and worlds are imagined, brought to life and experienced. We create for every age and audience, anchored by the strength of our content and experiences and the depth of our connection with fans. We are creator-first, audience-focused, tech-forward, globally scaled.
Here, you’ll work with talented teams that move fast, think boldly and collaborate with purpose to deliver results. We aim high, champion the best ideas and win together, earning the trust of our employees, creators, partners and audiences every day.
If you’re energized by the opportunity to help build the next-generation global media and entertainment company powered by creativity and technology, we’d be thrilled to welcome you aboard. LET’S GO!
We are the now and the next. The power behind the people building the future. We are born from the spirit of innovation. We are created from the idea that people around the world want more, need more, deserve more. We are the home of the global digital revolution. We are CNN. ㅤ
About the Team
With deep domain expertise, advanced technical capabilities, and a proven track record of successful collaborations, the AI Enablement & Machine Learning team at CNN is accelerating our digital transformation through strategic applications of machine learning and AI technologies.
The ML Platform group within ML Foundations builds and maintains the infrastructure, deployment tooling, and observability that enable CNN's Machine Learning and AI Systems teams to move from prototype to production with velocity and confidence. We support diverse model architectures — two-tower, bandits, LLM- based systems, and traditional ML — across rapid experimentation and scaled production deployment.
Our vision is that CNN's ML and AI teams operate with velocity and confidence, supported by infrastructure that handles everything from rapid experimentation to scaled production deployment across diverse model types and use cases.
Your New Role...
As a Staff Software Engineer on ML Platform, you will work across teams to design, build, and operate the infrastructure foundations that power model training, serving, experimentation, and observability for our Machine Learning and AI Systems teams.
You will partner with ML engineers, data engineers, and AI Systems engineers to understand production needs, build reliable infrastructure, and deliver tooling that accelerates the team.
Key challenges you will tackle:
Outerbounds Migration: Own end-to-end migration of CNN's ML training and orchestration workloads to Outerbounds-managed Metaflow, with zero production disruption and a clear path to self-service for ML practitioners.
Observability and Cost Attribution: Establish comprehensive observability across all ML products, AI applications, and shared infrastructure — including the monitoring, alerting, and diagnostic tooling engineers need to operate production systems reliably, and cost attribution that lets us understand and govern ML/AI spend by team, product, and use case.
Model and Application Registry:
Design and operate a unified registry and versioning system for ML models and AI applications, providing lineage, reproducibility, and a clean handoff between development and production.
Feature Resolution Framework: Evolve our existing feature resolution framework from a loosely coupled set of pipelines into a real platform — one that lets ML and AI Systems engineers configure content types and events to intercept, register feature-generation APIs, and land resolved features as durable data products in the feature store. The features this framework produces — ML- and LLM-generated alike — power everything from analytics to training to inference to user-facing rendering.
What You'll Do
Design and own infrastructure, deployment tooling, and developer experience for ML and AI Systems teams
Lead architectural…