This is a full-time hybrid role as an ML Ops Engineer with expertise in SageMaker or MRM, based 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. You will collaborate with data scientists, ML engineers, and IT professionals to ensure that machine learning models are seamlessly integrated into production systems and perform at scale.
Qualifications
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.