Software Engineer II: AI​/ML Personalized Content

Position: Software Engineer II: AI/ML for Personalized Content
Welcome to Warner Bros. Discovery… the stuff dreams are made of.
Who We Are…
When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the  storytellers  bringing our characters to life, the  creators  bringing them to your living rooms and the  dreamers  creating what’s next…
From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive.
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.
To see what it’s like to work atCNN, follow @WBDLife on Instagram and X !
With deep domain expertise, advanced technical capabilities, and a proven track record of successful collaborations, the AI Enablement C Machine Learning team at CNN is accelerating our digital transformation through strategic applications of machine learning and AI technologies. Our current products include popular, related and personalized content recommendations, contextual ad targeting, and site search-serving millions of CNN users via CNN web and mobile apps.

Within the next quarter, we will be launching summarization and classification features with chat to follow early next year.
We have a variety of specializations and collaborate closely, enhancing our platform and adding to the suite of machine learning features running on it.
Machine learning engineers (MLEs) build models and features
Data engineers fulfill the availability and latency requirements provided by MLEs
Some software engineers partner with MLEs to operationalize and expose models and features
Other software engineers focus on our ML platform and tooling, including A/B testing

Here are some of the key challenges the team will tackle in next couple of quarters:
Content   Summaries :
Support testing and adoption of various types of content summaries from multiple domains, which can be leveraged in consumer experiences along with embedding generation and classification.
Two-Tower   Experimentation :
Explore options for incorporating additional user context in our personalized recommendations model such as geolocation, time of day and time of year
All Access Search :
Partner with teams across CNN to design and build a roadmap for CNN streaming content search.
Bandit   Foundation :
Enhance data access and begin experimenting with bandits for online ranking of recommendations
Optimize Site Performance:  Dynamically deliver personalized content alongside cached assets, improving load times and enhancing user experience with features like page-level deduplication
About the Job  As a Software Engineer II, you will have many opportunities to collaborate with other engineers across the team.
Here are some specific expectations of this role.
Promote an inclusive and supportive engineering culture on the team
Solve business problems with simple and straightforward solutions
Strive for operational excellence--building highly available, low latency, and efficient software with support from other engineers
Build subject matter expertise related to multiple production systems
Communicate effectively—through progress updates, timely requests for support, demos, and technical documentation
Author, test, review, and optimize production-quality code, following best practices for IaC, version control, and continuous delivery with support from other engineers
Be passionate about software engineering with a strong sense of responsibility for the code you and your team write, delivering high-quality results that improve with each iteration
Embrace failure as a learning opportunity—use research and experimentation to choose the best solutions that meet business goals, moving autonomously from proof-of-concept to…