Director, Machine Learning Engineering, CNN Digital Products & Services

Your New Role The Director, ML / AI leads this technical and people agenda: you set direction for ML and AI across CNN’s digital products, align roadmaps with engineering, analytics, product, and editorial partners, and ensure that what we ship is measurable, reliable, and worthy of a global news brand. Your Role Accountabilities You will be responsible for ensuring excellent ML/AI methods for CNN’s consumer and editorial surfaces: a coherent portfolio across personalization, search, recommendations, content understanding, and responsible use of generative AI and foundational models. You combine people leadership with credible technical judgment: you build and develop machine learning engineers, set cross‑team priorities, and stay hands‑on enough to arbitrate architecture and modeling decisions when it matters. Strategic Priorities ML and AI thought leadership Partner with product and editorial teams to develop new uses for machine learning and AI tools across CNN’s internal and customer‑facing environments. Platform and data partnership Co‑own roadmaps with data engineering and analytics so instrumentation, pipelines, feature paths, telemetry, and data quality keep pace with ML – without excellent data and platform partnership, ML leadership cannot succeed. Experimentation at scale Champion rigorous testing, and machine‑learned targeting, in coordination with Data & Analytics, and clear decision rights so we learn fast without shipping confusion. Performance and scale Ensure ML‑powered experiences work within real‑time and web‑scale constraints—alongside caching, edge delivery, and high availability for millions of users. Sustainability Balance innovation with maintainability and cost – leverage cloud and open‑source capabilities responsibly. Day‑to‑Day Responsibilities Lead, hire, and develop machine learning engineers; foster an inclusive culture that provides career growth and guidance for MLEs at all levels while pushing the boundaries on new methodologies and technologies. Partner with product and analytical teams to pioneer new uses of ML and optimize existing use cases. Own the ML systems roadmap with platform, data, and product leadership; size opportunities, prioritize capabilities, and secure alignment and resourcing with senior stakeholders. Partner with platform, infrastructure, and ML platform teams on training, serving, feature pipelines, and operational needs for personalization and search. Partner with downstream application teams on stable interfaces between ML capabilities and the website, mobile apps, and editorial tools. Guide design and delivery of ML in production: monitoring, validation, iteration based on live impact—not offline metrics alone. Represent ML/AI clearly to editorial and business audiences; translate goals into investments and non‑negotiables (trust, corrections, safety). Respond to incidents and learning cycles at the organizational level; champion improvements to developer experience, integrations, and testing. Approach We Value Author, review, and optimize production‑quality code and systems that adhere to industry standards and best practices. Demonstrate passion for software and ML engineering, with a strong sense of responsibility for what you and your team ship. Take ownership of issues and advocate for your team and products; embrace failure as a learning opportunity and use research and experimentation to choose solutions that meet company goals. Follow a progressive development methodology—proof‑of‑concept to prototype to production—with measurable milestones. Enhance the effectiveness of your team and partners by sharing knowledge, explaining complex technologies in simple terms, and driving sound technical decisions. Collaborate across functions, squads, teams, and organizations to best serve our users. Qualifications & Experience Advanced degree (Master’s or PhD) in Computer Science, Mathematics, Statistics, Information Science, Engineering, or another quantitative discipline—or equivalent depth from industry experience. PhDs and research‑heavy backgrounds are welcome. 8+ years of professional experience building machine learning and data‑science‑driven systems with a proven record of innovation and measurable product or business impact. Candidates with a PhD may qualify with 6+ years of strong industry experience post‑degree if the depth is equivalent. 5+ years developing and deploying AI/ML systems across the full lifecycle—ideation, proof of concept, deployment, monitoring, and iteration—in Python. Demonstrated technical leadership: a sustained record of leading multi‑engineer initiatives, setting technical direction for ML systems, mentoring senior engineers, and partnering across product and platform—through people management, staff/principal‑level scope, or an equivalent combination. Formal people‑management experience is valued but not strictly required for candidates with an exceptional senior or staff ML track record who are ready to step into a director role. Experience deploying complex, large‑scale machine learning systems in production; practical familiarity with ML modeling and the operational realities of live models. Strong communication skills and the ability to build trusted partnerships across functions in a fast‑paced, high‑energy environment. The Nice to Haves Experience from large‑scale consumer internet environments—social, streaming, marketplaces, or similar—where ranking, retrieval, recommendations, or search operate under latency, safety, and experimentation constraints. Experience with recommendation, search, or ad‑serving algorithms and systems; NLP, information retrieval, or related areas. Familiarity with data pipelines, feature stores, embedding infrastructure, or large‑scale feature serving. Deep familiarity with experimentation frameworks and A/B testing methodologies. Interest in media, publishing, or news; commitment to responsible AI and high‑trust content experiences. Exposure to generative AI in product settings—guardrails, evaluation, latency and cost tradeoffs, human‑in‑the‑loop workflows. Experience with Agile delivery practices. How We Get Things Done This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request. In compliance with local law, we are disclosing the compensation, or a range thereof, for roles in locations where legally required. Actual salaries will vary based on several factors, including but not limited to external market data, internal equity, location, skill set, experience, and/or performance. Base pay is just one component of Warner Bros. Discovery’s total compensation package for employees. Pay Range: $234,500.00 – $435,500.00 salary per year. Other rewards may include annual bonuses, short‑and‑long‑term incentives, and program‑specific awards. In addition, Warner Bros. Discovery provides a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, a retirement savings plan, paid holidays and sick time and vacation. #J-18808-Ljbffr