Real time Machine learning Engineer (RTML Engineer)

InfoVision - Irving, TX

Full-time

Irving, TX

Professional, Scientific, and Technical Services

About the position

The Real Time Machine Learning Engineer (RTML Engineer) position is a critical role focused on the development and deployment of machine learning models in real-time environments. This position requires a strong foundation in computer science and engineering principles, as well as specialized knowledge in artificial intelligence and machine learning practices. The RTML Engineer will be responsible for designing, implementing, and maintaining scalable machine learning systems that can operate efficiently in cloud-based environments. The role involves collaborating with data scientists and software engineers to ensure that machine learning models are effectively integrated into production systems, providing real-time insights and analytics to drive business decisions. In this role, the engineer will leverage their expertise in real-time model serving and cloud-based frameworks to develop robust applications that can handle large volumes of data. The RTML Engineer will also be tasked with monitoring system performance, collecting real-time statistics, and troubleshooting any issues that arise during the deployment of machine learning models. A solid understanding of Kubernetes (K8s) architecture and operations is essential, as the engineer will be deploying applications in production K8s clusters and ensuring they are configured correctly for optimal performance. The ideal candidate will have a strong background in software development, particularly in AI and machine learning, and will be comfortable working in fast-paced environments where they can apply their skills to solve complex problems. This position offers the opportunity to work on cutting-edge technology and contribute to the advancement of machine learning applications in real-time scenarios.

Responsibilities

• Design and implement real-time machine learning models for production environments.
• Collaborate with data scientists to integrate machine learning models into applications.
• Monitor system performance and collect real-time statistics for analysis.
• Troubleshoot issues in deployed applications and optimize performance.
• Deploy large applications in production Kubernetes clusters and ensure proper configuration.
• Develop and maintain cloud-based frameworks for machine learning applications.

Requirements

• Bachelor's degree or above in Computer Science, Engineering, or related fields.
• Four or more years of work experience in software development.
• At least two years of experience in AI/ML engineering with a good understanding of data science practices.
• Strong expertise in real-time machine learning model serving and cloud-based framework development.
• Proficiency in programming languages such as Python and Java.
• Experience in large application development in cloud environments like AWS, GCP, and on-premises clusters.
• Hands-on experience with Kubernetes architecture and operations.

Nice-to-haves

• Basic understanding of real-time feature engineering methodologies and practices.
• Experience with performance monitoring methods for real-time systems.