Engineer II, Machine Learning Software

Samsung Electronics America is seeking an Engineer II, Machine Learning Software to join their team in Mountain View, CA. This role presents an exciting opportunity to work at one of the world's leading technology companies, focusing on building next-generation machine learning infrastructure.

The position involves designing and developing a cutting-edge machine learning platform capable of supporting thousands of concurrent model training pipelines and handling trillions of daily batch predictions. You'll be instrumental in building a world-class ML platform specifically tailored for Samsung's ML-based advertising business, with the goal of significantly improving the model development and deployment process.

As an Engineer II, you'll be working with state-of-the-art technologies including Docker, cloud platforms (AWS, Google Cloud), and modern monitoring tools like Prometheus and Grafana. The role requires a strong background in software engineering and machine learning, with a Master's degree in Computer Science or related field and three years of relevant experience (or Ph.D. with one year of experience).

Key responsibilities include researching the latest ML platform technologies, creating prototypes, collaborating with internal ML teams to improve code quality, and working with global cross-functional teams. You'll also maintain the ML platform codebase and pipelines while ensuring high availability and quality for both online and offline production systems.

This is an excellent opportunity for someone who wants to work at the intersection of machine learning and software engineering, making a direct impact on Samsung's advertising technology infrastructure. The role offers competitive compensation ($199,534 - $204,000/year) and the chance to work with a diverse, innovative team in Silicon Valley.

Samsung Electronics America is committed to fostering an inclusive culture and provides equal employment opportunities to all individuals. They offer reasonable accommodations for qualified individuals with disabilities during the application process, demonstrating their commitment to accessibility and support for their workforce.