Warner Bros.
Staff Mle, Personalization, Content Discovery
Every great story has a new beginning. Warner Bros. Discovery is a premier global media and entertainment company offering audiences the world's most differentiated and complete portfolio of content, brands and franchises across television, film, sports, news, streaming and gaming. Our mission is simple. To be the world's best storytellers with world-class products for consumers. From brilliant creatives to technology trailblazers and beyond, join us as we step into the next chapter. Warner Bros. Discovery's DTC technology and product organization sits at the intersection of tech, entertainment, and everyday utility. We are continuously leveraging new technology to build immersive and interactive viewing experiences. Our platform covers everything from search, content catalog, video transcoding, to personalization, global subscriptions, and more. We are committed to delivering unique and quality user experiences, ranging from video streaming to applications across connected TV, mobile, web and consoles. As a pure tech organization, we are essential to Warner Bros. Discovery's continued growth, building world-class streaming products from the ground-up for our iconic brands like HBO Max, Discovery Channel, CNN, Food Network, HGTV, Eurosport, MotorTrend, and many more. About You:
We are looking for a passionate Machine Learning Engineer to build and scale the DTC personalization models and algorithms for our new global streaming app, Max, as well as any future DTC streaming apps. You are excited about working in an environment that fosters innovation via prototyping, development, experimentation, and productionization. You will bring the right balance between rapid feature iteration and building a common set of platforms and tools to move quickly in the future. In your role, you will be working alongside a team of passionate machine learning engineers and applied Machine Learning researchers to build and contribute to architecting a system that serves millions of users worldwide. Responsibilities:
Architect, build and scale a recommendation system that powers the state-of-the-art personalization experience to users across Max, HBO, Discovery+ and other WBD offerings
Collaborate with ML/Ops engineers to develop and improve core components, infrastructure and architecture to train, deploy and serve models at scale
Collaborate with other data scientists, engineers, product teams and other key stakeholders and drive ML projects from conception to completion
Author, test, review, and optimize production-level code in Python, Go and Java while executing best practices in version control and code integration
Use and build upon open-source cloud computing technologies
Participate and support engineering leaders in strategic planning and demonstrate good judgment in setting and delivering against strategic goals for the team
Motivate, inspire and create a culture of experimentation and data-driven innovation while constantly striving to be an advocate for doing what is right for our customers
Requirements:
8+ years of industry experience, with 4+ years as tech lead experience (preferred)
Deep practical knowledge of modern machine learning lifecycle.
Deep practical knowledge of large-scale recommender systems, or large-scale ML ranking/retrieval/targeting systems and familiarity with A/B Tests and hypothesis testing is preferred
Experience with design, implementation, and performance tuning of ML models.
5+ years of programming experience in at least one of the following: Python/Java/Go with ability to rapidly prototype ideas and refine towards production.
Deep practical knowledge of large-scale recommender models and systems, or large-scale ML ranking/retrieval/targeting systems.
Experience with one of the cloud platforms AWS/GCP/Azure
Good practical knowledge of SQL and relational databases.
Experience with CI/CD tools like GitHub Actions, Jenkins, etc.
Excellent written and verbal communications skills, be comfortable presenting to large audiences.
Advanced degree (M.S.), or equivalent industry experience in statistics, computer science, machine learning or related fields.
Every great story has a new beginning. Warner Bros. Discovery is a premier global media and entertainment company offering audiences the world's most differentiated and complete portfolio of content, brands and franchises across television, film, sports, news, streaming and gaming. Our mission is simple. To be the world's best storytellers with world-class products for consumers. From brilliant creatives to technology trailblazers and beyond, join us as we step into the next chapter. Warner Bros. Discovery's DTC technology and product organization sits at the intersection of tech, entertainment, and everyday utility. We are continuously leveraging new technology to build immersive and interactive viewing experiences. Our platform covers everything from search, content catalog, video transcoding, to personalization, global subscriptions, and more. We are committed to delivering unique and quality user experiences, ranging from video streaming to applications across connected TV, mobile, web and consoles. As a pure tech organization, we are essential to Warner Bros. Discovery's continued growth, building world-class streaming products from the ground-up for our iconic brands like HBO Max, Discovery Channel, CNN, Food Network, HGTV, Eurosport, MotorTrend, and many more. About You:
We are looking for a passionate Machine Learning Engineer to build and scale the DTC personalization models and algorithms for our new global streaming app, Max, as well as any future DTC streaming apps. You are excited about working in an environment that fosters innovation via prototyping, development, experimentation, and productionization. You will bring the right balance between rapid feature iteration and building a common set of platforms and tools to move quickly in the future. In your role, you will be working alongside a team of passionate machine learning engineers and applied Machine Learning researchers to build and contribute to architecting a system that serves millions of users worldwide. Responsibilities:
Architect, build and scale a recommendation system that powers the state-of-the-art personalization experience to users across Max, HBO, Discovery+ and other WBD offerings
Collaborate with ML/Ops engineers to develop and improve core components, infrastructure and architecture to train, deploy and serve models at scale
Collaborate with other data scientists, engineers, product teams and other key stakeholders and drive ML projects from conception to completion
Author, test, review, and optimize production-level code in Python, Go and Java while executing best practices in version control and code integration
Use and build upon open-source cloud computing technologies
Participate and support engineering leaders in strategic planning and demonstrate good judgment in setting and delivering against strategic goals for the team
Motivate, inspire and create a culture of experimentation and data-driven innovation while constantly striving to be an advocate for doing what is right for our customers
Requirements:
8+ years of industry experience, with 4+ years as tech lead experience (preferred)
Deep practical knowledge of modern machine learning lifecycle.
Deep practical knowledge of large-scale recommender systems, or large-scale ML ranking/retrieval/targeting systems and familiarity with A/B Tests and hypothesis testing is preferred
Experience with design, implementation, and performance tuning of ML models.
5+ years of programming experience in at least one of the following: Python/Java/Go with ability to rapidly prototype ideas and refine towards production.
Deep practical knowledge of large-scale recommender models and systems, or large-scale ML ranking/retrieval/targeting systems.
Experience with one of the cloud platforms AWS/GCP/Azure
Good practical knowledge of SQL and relational databases.
Experience with CI/CD tools like GitHub Actions, Jenkins, etc.
Excellent written and verbal communications skills, be comfortable presenting to large audiences.
Advanced degree (M.S.), or equivalent industry experience in statistics, computer science, machine learning or related fields.