GenAI

Responsibilities:

• Build and maintain scalable infrastructure for machine learning model & pipeline deployment, including containerization & orchestration.
• Develop and maintain scalable & secure REST APIs for serving multiple machine learning models to various users.
• Collaborate with data scientists and software engineers to ensure seamless integration of ML models into our systems.
• Design and optimize data pipelines, data storage, and data processing systems to support the training and inference processes of machine learning models.
• Build and maintain data and model dashboards to monitor model performance and health in production environments.
• Collaborate with cross-functional teams to identify and address data quality, data governance, and security considerations in the context of ML operations.

Requirements:

• Required
  • Bachelor's degree in Computer Science, Data Science, or a related field. A Master's or Ph.D. degree is a plus.
  • 5+ years of hands-on experience in ML operations, ML engineering, or related roles.
  • Experience with AWS or Azure cloud platforms, specifically AWS Sagemaker
  • Experience with REST API development, AWS Networking Protocols
  • Solid understanding of infrastructure components and technologies, including containerization (e.g., Docker) and CI/CD pipelines
  • Strong knowledge of software engineering principles and best practices, including version control, code review, and testing.
  • Excellent problem-solving skills, with the ability to analyze complex issues and provide innovative solutions in a fast-paced environment.
  • Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams and stakeholders