Sr Machine Learning Engineer - Recommendations (Max)
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, and 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.
We are looking for a passionate Machine Learning Engineer to build and scale the DTC personalization systems and services 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 productionalization. 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 researchers to build and contribute to architecting a system that serves millions of users worldwide.
• Architect, build and scale a recommendation system that powers a state of the art personalization experience to users across Max, HBO, Discovery+ and other WBD offerings
• Collaborate with other ML/Ops engineers to develop and improve core components, infrastructure and architecture to train, deploy and serve models at scale
• Lead architecture improvements for our personalization services and infrastructure
• Collaborate with 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
• Mentor, influence engineers across organizations and lead by example with high quality examples of your work at the organization level
• 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
• 4+ years of industry experience in Machine Learning, with 3+ years leading organization wide projects with multiple stakeholders.
• Deep practical knowledge in modern machine learning lifecycle.
• 4+ 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 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.
• Experience with design, implementation, and performance tuning of ML models.
• 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
• Excellent written and verbal communications skills, be comfortable presenting to large audiences.
• Advanced degree (M.S.), or equivalent industry experience in software engineering, computer science, machine learning or related fields
If you're a qualified candidate and you require adjustments or accommodations to search for a job opening or apply for a position, please contact us at firstname.lastname@example.org.
Jobcode: Reference SBJ-r14xmm-44-197-101-251-42 in your application.