Manager, Software Engineering, AI Enablement & Machine Learning

Warner Bros. Discovery•Atlanta, GA

About The Position

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 at CNN, follow @WBDLife on Instagram and X! 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. 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 Your New Role... The team is composed of multiple squads: a platform squad along with cross-functional squads that leverage the platform to develop products. As the Engineering Manager for a products squad, you will manage 2+ engineers with varied backgrounds and focuses: 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 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 incorporate streaming content and add support for OTT 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

Requirements

8+ years progressively complex experience designing, building, and shipping products
5+ years backend engineering experience with data-heavy applications
3+ years of experience with IaC, deployment pipelines, and relational databases
5+ years of experience managing engineering teams
Experience partnering with and / or leading ICs responsible for machine learning model development (data scientists, MLEs, etc.)
Familiarity with ML specific pipelines and tooling
Familiarity with experimentation frameworks and A/B testing methodologies
Deep understanding of common software data structures and algorithms, with extensive experience in modern development technologies and practices
A proven track record of building web scale products that are highly available and performant
Passion for growing engineers through mentorship, talent acquisition, and professional development
A collaborative mindset, understanding that great results come from teamwork and a positive culture
Proven success leading complex projects within an engineering team: knowing when to handle issues independently, when to rally the right people for alignment, and when to escalate
Excellent communication, presentation, and documentation skills

Nice To Haves

Practical experience with recommendations, search and/or personalization
Practical experience building cost-effective ML solutions at scale
Experience with RAG pipelines, feature stores, or embedding infrastructure

Responsibilities

Support, coach, mentor, and provide valuable feedback to the individuals you manage to help them excel
Work with cross-functional partners and stakeholders on activities such as planning, technical strategy, quality and delivery
Partner with engineers within the team and across the organization to build and integrate machine learning features into our site, apps, and editorial tools
Lead other engineers on the team by example, code reviews, and coaching, ensuring that code is readable, maintainable, scalable, observable, and resilient
Champion improvements to developer experience, integrations, and testing processes
Leverage vended and open-source cloud technologies to reduce maintenance costs and improve efficiencies, ensuring our products remain profitable
Collaborate with other engineers to develop and enhance core capabilities, infrastructure, and architecture
Author, review, and optimize production-quality code that adheres to industry standards and best practices (IaC, CICD, etc.)
Demonstrate a passion for software engineering, with a strong sense of responsibility for the code you and your team write
Take ownership of issues and be a strong advocate for your team and the products
Embrace failure as a learning opportunity—use research and experimentation to ultimately choose the best solutions that meet company goals
Follow a progressive development methodology, moving from proof-of-concept to prototype to production release
Enhance the effectiveness of your squad, the team, and our partners by sharing your knowledge, communicating about complex technologies and problems in simple terms, and driving technical decisions
Collaborate across functions, squads, teams, and organizations to best serve our users