Machine Learning Model Engineer

Samsung Ads is seeking a Machine Learning Model Engineer to join their Platform Intelligence (PI) team in a role that combines advanced ML technology with real-world advertising applications. This position offers a unique opportunity to work with Samsung's proprietary data and develop large-scale machine learning products that have direct business impact.

The role is situated within Samsung Ads, an advanced advertising technology company experiencing rapid growth. The company focuses on connecting brands with Samsung TV audiences through data-driven advertising solutions. As part of the Platform Intelligence team, you'll be at the forefront of applying cutting-edge machine learning techniques to improve existing systems and create new revenue streams.

The position requires a blend of technical expertise and leadership skills. You'll be responsible for leading a team in delivering production-grade machine learning solutions, working closely with various stakeholders, and managing the entire ML pipeline from conception to deployment. The role involves hands-on work with state-of-the-art technologies while also requiring strategic thinking to align technical solutions with business objectives.

Key technical aspects include working with mainstream ML libraries (TensorFlow, PyTorch, Spark ML), big data tools (MapReduce, Spark, Flink, Kafka), and programming in languages like Python and Go. The role demands both depth in machine learning theory and breadth in practical implementation skills.

The compensation package is competitive, ranging from $190,000 to $280,000 for candidates based in Mountain View, CA, with comprehensive benefits including medical, dental, vision, life insurance, 401(k), and various other perks. The position offers a hybrid work arrangement, combining the flexibility of remote work with in-person collaboration.

This is an excellent opportunity for someone who wants to work at the intersection of machine learning and advertising technology, with access to unique datasets and the chance to make significant impact in a rapidly growing field. The role offers both technical challenges and leadership opportunities, making it ideal for someone looking to advance their career in applied machine learning.