Requirements

Expected technologies

Terraform

Our requirements

• 6+ years of industry experience with a Master's degree or 3+ years of industry experience with a PhD degree.
• Extensive industry experience with Infrastructure as Code (Terraform), orchestration tools ( Airflow, AWS Step/Lambda), building CI/CD pipelines using Github Actions, and real-time monitoring/alerting framework such as Prometheus and Grafana.
• Familiarity with CI/CD, ETL, big data tools, and mainstream ML libraries (e.g., MapReduce, Spark, Flink, Kafka, Docker, Kubernetes, TensorFlow, PyTorch, Spark ML, etc.).
• Hands-on experience with machine learning related frameworks (e.g., TensorFlow, PyTorch, model registry, OpenMetadata, ML feature store).
• Solid theoretical background in machine learning or data mining and strong conceptual, problem solving, and analytical skills.
• Extensive programming experience in Python, Go or other OOP languages, SQL and database, and familiarity with data structures, algorithms and software engineering principles.
• Strong communication and interpersonal skills to drive cross-functional partnerships.
• Ability to work in a fast-paced environment, quickly debug issues, provide proof-of-concept solutions and apply the changes to production.

Optional

• Extensive experience with Snowflake, Snowpark, and Redis/Aerospike.
• Knowledge about Amazon Web Services (AWS).
• Experience with the advertising industry and real-time bidding (RTB) ecosystem.

Your responsibilities

• Design and develop the next generation machine learning platform to support thousands of model training pipelines concurrently and trillions of daily batch predictions.
• Build a world-class ML platform tailored for Samsung’s ML based advertising business, which can significantly improve the lead time for model end-to-end development and deployment process.
• Research the latest machine learning platform technologies in the industry and create quick prototypes / proof-of-concepts.
• Closely work with different internal ML teams (e.g., ML serving and MLOps teams) to improve our codebase, product health, and ensure the best engineering quality
• Closely work with cross-functional partner teams in global settings to deliver new ML features and solutions and achieve business objectives.
• Mentor junior engineers and provide technical guidance.
• Learn quickly and adapt to a fast-paced working environment.