Manager, Software Engineering, AI Enablement & Machine Learning

Warner Bros. Discovery•Atlanta, GA

About The Position

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 ML 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. This year we are partnering with teams across the company to democratize AI at CNN. Our "multiplier" approach allows our team to have outsized organizational impact by providing domain expertise, enabling teams, collaborating deeply, and building shared infrastructure. 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 5+ engineers with varied backgrounds and focuses: Machine learning engineers focusing on traditional model development and AI engineering with foundational models Engineers of various backgrounds who are now focused on AI integrations Backend engineers focusing on data availability, API development and client integrations Full stack engineers who contribute to our CMS You will collaborate effectively with product managers, program managers, designers and engineers across squads and teams to plan and execute on traditional machine learning and AI engineering with foundational models. And you will grow the squad as needed to support the increasing demand for machine learning work. Here are some of the key challenges our team will tackle this year: Launch Recommendations Autofill: Support testing and adoption of a CMS component that will allow programming and editorial staff to add several types of recommendations anywhere on the site, filtering by attributes like content type and section. Launch Editorially Curated Homepage Module: Support testing and adoption of a CMS component that will allow editorial to curate a candidate pool and pin items and recommend from that pool. Enhance Site Search: Add CTV content types, add keyword / multi-stage search, and implement a number of other enhancements that our product team is planning now. Experiment with Two-Tower: Incorporate additional user context in our personalized recommendations model such as geolocation, time of day and time of year Build Bandit Foundation: Partner with the platform squad to 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