At Warner Music Group, we’re a global collective of music makers and music lovers, tech innovators and inspired entrepreneurs, game-changing creatives and passionate team members. Here, we turn dreams into stardom and audiences into fans. We are guided by three core values that underpin everything we do across all our diverse businesses: • Curiosity: We do our best work when we’re immersing ourselves in culture and breaking through barriers. Curiosity is the driving force behind creativity and ingenuity. It fuels innovation, and innovation is the key to our future. • Collaboration: Making music and bringing it to the world is all about the power of originality amplified by teamwork. A great idea, like a great song, travels globally. We ignite passions and build connections across our diverse community of artists, songwriters, partners, and fans. • Commitment: We pursue excellence for our team and our talent. Everything in music starts with a leap into the unknown, and we’re committed to keeping the faith, acting with integrity, and delivering on our promises. Technology is one of the most important parts of our business. Whether it’s signing up new artists; ensuring we provide the right data to Spotify, YouTube, and other digital service providers; or helping artists use the latest AI tools and make thoughtful decisions with data-driven insights – technology plays an invaluable role in our success. The engineering team at Warner Music Group makes all of it a reality. WMG is home to a wide range of artists, musicians, and songwriters that fuel our success. That is why we are committed to creating a work environment that actively values, appreciates, and respects everyone. We encourage applications from people with a wide variety of backgrounds and experiences. Consider a career at WMG and get the best of both worlds – an innovative global music company that retains the creative spirit of a nimble independent. At Warner Music Group, we are building cutting edge inference systems to better understand the landscape of music consumption toward the goal of providing actionable insights that drive business growth. We are hiring talented Machine Learning Engineers to collaborate with our Data Science and Data Platform teams in order to build scalable Machine Learning systems that enable rapid iteration, experimentation, and continual improvement in our modeling efforts. Our ideal candidate will have strong ML and Data Science skills along with experience and a passion for building efficient, robust software.
Responsibilities:
Develop a strong understanding of the business problems we are trying to solve.
Together with tech leadership and data scientists, identify the business problems that are amenable to machine learning solutions. Then own models for those solutions end to end: define, design, train, evaluate, launch, maintain, improve.
Together with tech leadership and data scientists, identify the systems we need that enable us to scale our model training, iteration, and serving capabilities. Then design, implement, and launch those systems.
Ensure that we are able to run modeling experiments and launches with maximal efficiency, quality, reliability, and repeatability in a large-scale environment with > 2TB of incoming data per day and a total corpus in excess of 20PB.
Mentor more junior MLEs and Data Scientists.
Work closely with cross-functional partners to define project objectives and deliverables.
Requirements:
9+ years of full-time hands-on experience building scaled ML systems, training large ML models, or equivalent experience.
Excellent coding and system design skills. Strong practical ML knowledge, working knowledge of ML theory and how it influences modeling choices.
Experience using LLMs and other AI techniques in practical contexts.
High sense of ownership and a drive to deliver impact in a fast-paced, evolving, ambiguous environment
Ability to collaborate closely with Data Scientists, Software Engineers, and Product Managers.
Strong communication skills and ability to influence roadmaps and ML strategy.
Experience with cloud computing services or platforms (preferably AWS)
Experience with both Snowflake and Databricks is a plus
Bachelor’s Degree or above in a quantitative field
