Machine Learning Operations Engineer

1 day ago


San Antonio, Texas, United States ExcelSoft Full time

Role Overview

ExcelSoft is seeking a highly skilled Machine Learning Operations Engineer to join our team in San Antonio, TX. As an ML Ops Engineer, you will be responsible for managing the machine learning lifecycle, with a focus on deploying, optimizing, and monitoring models using AWS SageMaker or MRM.

Key Responsibilities

  • Collaborate with data scientists, ML engineers, and IT professionals to ensure seamless integration of machine learning models into production systems.
  • Develop and maintain CI/CD pipelines for ML models, leveraging containerization tools like Docker and Kubernetes.
  • Design and implement cloud-based infrastructure for ML workloads, utilizing AWS SageMaker and cloud deployment strategies.
  • Work closely with cross-functional teams to ensure data management, engineering concepts, and MLOps best practices are followed.
  • Stay up-to-date with industry trends and advancements in ML frameworks, programming languages, and cloud platforms.

Requirements

  • Strong expertise in AWS SageMaker or MRM.
  • Proficiency in programming languages such as Python, Java, or Scala.
  • Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
  • Knowledge of cloud platforms, especially AWS (SageMaker), and cloud deployment strategies.
  • Familiarity with containerization tools such as Docker and Kubernetes.
  • Experience in building and maintaining CI/CD pipelines for ML models.
  • Strong understanding of data management, engineering concepts, and MLOps best practices.
  • Excellent problem-solving and analytical skills.
  • Strong communication and collaboration abilities.
  • Bachelor's degree in Computer Science, Engineering, or a related field.


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