Position Summary
Samsung Ads is an advanced advertising technology company in rapid growth that focuses on enabling advertisers to connect audiences from Samsung devices as they are exposed to digital media, using the industry’s most comprehensive data to build the world’s smartest advertising platform. Being part of an international company such as Samsung and doing business around the world means that we get to work on big, complex projects with stakeholders and teams located around the globe.Role and Responsibilities
Machine learning lies at the core of the advertising industry, and this is no exception to Samsung Ads. At Samsung Ads, we are actively exploring the latest machine learning techniques to improve our existing systems and products and create new revenue streams. As a machine learning platform engineer of the Samsung Ads Platform Intelligence (PI) team, you will have access to unique Samsung proprietary data to develop and deploy a wide spectrum of large-scale machine learning products with real-world impact. You will work closely with and be supported by a talented engineering team and top-notch researchers to work on exciting machine learning projects and state-of-the-art technologies. You will be welcomed by a unique learning culture and creative work atmosphere. This is an exciting and unique opportunity to get deeply involved in envisioning, designing and implementing cutting-edge machine learning products with a fast growing team.
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.
Experience Requirements:
6+ years of industry experience with a Master's degree or 3+ years of industry experience with a PhD degree in Computer Science or related fields such as Statistics, Data Science, Technology, Engineering and Mathematics.
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.
Skills and Qualifications
Preferred Experience Requirements:
Extensive knowledge of Amazon Web Services (AWS) is a huge plus.
Extensive experience with Snowflake, Snowpark, and Redis/Aerospike.
Experience with the advertising industry and real-time bidding (RTB) ecosystem.
Salary Range Pay Transparency: Compensation for this role, for candidates based in Mountain View, CA is expected to be between $240,000 and $280,000. Actual pay will be determined considering factors such as relevant skills and experience, and comparison to other employees in the role. Regular full-time employees (salaried or hourly) have access to benefits including: Medical, Dental, Vision, Life Insurance, 401(k), Employee Purchase Program, Tuition Assistance (after 6 months), Paid Time Off, Student Loan Program (after 6 months), Wellness Incentives, and many more.
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