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Staff Machine Learning Engineer
Warner Bros. Discovery
- +1
- +5
- United States
- +1
- +5
- United States
About
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
and
X !
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. 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 Staff MLE, you will work across our team and collaborate with engineering leads on other teams to drive technical excellence, facilitate growth and promote an inclusive and supportive engineering culture.
• Design and deliver ML components within our services against product requirements—explore data, identify gaps, and prepare it for machine learning models • Implement model training processes on a schedule in production with monitoring and validation to assess model and system performance • Take full ownership of problems with ML scope—devise solutions based on limited information, adapt existing approaches, and use judgment to select the right course of action. Help others understand ML components within our larger systems and products • Design components and systems architecture, driving technical decisions that create functional-level impact and deliver complex features in partnership with platform 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. Author, test, review, and optimize production-quality code, following best practices including version control, and continuous delivery • Communicate effectively across different audiences—whether through technical documentation, code reviews, design reviews, or interactions with stakeholders and adjacent teams • Embrace failure as a learning opportunity—use research and experimentation to choose the best solutions that meet company goals, moving autonomously from proof-of-concept to production release
The Essentials
• Bachelor's Degree AND 5+ years of related experience or Master's Degree AND 3+ years of related experience, in Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience with machine learning, artificial intelligence, statistics, predictive analytics, research) • 5+ years of industry software engineering experience in one or more languages, preferably with extensive python experience
• 3+ years experience developing and deploying AI/ML products or systems at multiple stages in the product cycle from ideation and proof of concept to deployment, monitoring, and iteration
The Nice to Haves
• Experience with NLP, information retrieval, or Recommendation Systems • Understanding of experimentation frameworks and A/B testing methodologies • Experience with data pipelines, feature stores, or embedding infrastructure • Background in media, publishing, or content recommendation systems
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
www.wbd.com/guiding-principles/
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: $145,600.00 - $270,400.00 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.
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Nice-to-have skills
- Artificial Intelligence
- Machine Learning
- Python
- Research
- Statistics
Work experience
- Machine Learning
Languages
- English
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