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# Engineer II, Machine Learning (mult.)

- **Company:** Samsung
- **Location:** Mountain View, CA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Amazon Web Services, Databases, Computer Engineering, Extract Transform Load (ETL), Data Mining, Data Structures, Apache Hadoop, Python (Programming Language), PostgreSQL, Machine Learning, MySQL, Tensorflow, Scala (Programming Language), SQL Databases, Test Data, Pytorch, Apache Spark, Deep Learning, Information Technology, Apache Flink, Apache Kafka, Data Management, Machine Learning Operations
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25303_152a0e17dd851fb2d5d5664353dcb7b2

## About the Role

Master's degree in Computer Science, Computer Engineering, or a related field and a minimum of 2 years of experience as an Engineer II or similar role in machine learning algorithm engineering.

 * Design and implement machine learning platforms, models, and algorithms.
 * Experience with deep learning frameworks, including TensorFlow and PyTorch.
 * Proficiency in programming languages such as Java, Python, and Scala.
 * Experience with ETL and big data tools, including Hadoop, Spark, Flink, and Kafka.
 * Experience with Amazon Web Services.
 * Strong knowledge of data structures and algorithms, data mining, and system design for machine learning.
 * Experience with SQL and database systems, including PostgreSQL and MySQL.

## Description

Design, iterate and fine-tune machine learning models with various computing resource constraints for deployment. Optimize the existing machine learning model architectures and algorithm implementations. Explore cutting-edge technologies and create quick prototypes. Design experiments, perform evaluations, and apply enhancements to products. Experiment with scalable machine learning architectures and platform tailored to environment and create quick prototypes / proof-of-concepts. Develop highly scalable machine learning pipelines and tools to support the development and deployment of machine learning products. Optimize the existing machine learning pipelines/platforms/architectures to meet real-world latency constraints. Research the state-of-the-art technology stack for machine learning applications. Develop and test data pipelines and services to support products. Research state-of-the-art data management techniques and tools and identify the optimal fit to improve the overall
performance of systems. Improve and maintain current pipelines and services in production. Design and perform complex analysis to determine resolutions that clarify and address operational and business concerns. Lead efforts related to the machine learning infrastructure/platform and collaborate with other internal and external collaborators.