Senior MLOps Engineer at Ascentt in Plano, Texas

Posted in Other 2 days ago.

Type: full-time





Job Description:

Job Title: MLOps Engineer

Location: Dallas, TX

Job Type: Full-time

Responsibilities:
  1. MLOps and DevOps Integration:
  • Design, implement, and manage end-to-end Machine Learning Operations (MLOps) processes.
  • Collaborate with cross-functional teams to integrate ML models seamlessly into production using tools such as GitHub Actions.
  1. Machine Learning Lifecycle Management:
  • Drive the implementation of best practices for ML model deployment, monitoring, and maintenance throughout the entire ML lifecycle.
  • Work closely with Data Scientists and DevOps teams to streamline the deployment process and ensure scalability.
  1. Infrastructure and Containerization:
  • Utilize Docker for containerization to ensure consistent and reproducible deployment environments.
  • Implement and maintain infrastructure as code using tools like Terraform.
  1. GitHub Actions and CI/CD:
  • Design and maintain robust CI/CD pipelines using GitHub Actions to automate the ML model deployment process.
  • Ensure efficient version control and collaboration among team members.
  1. Amazon SageMaker Expertise:
  • Possess a deep understanding of Amazon SageMaker for scalable and cost-effective ML model training and deployment on AWS.
  • Optimize and fine-tune SageMaker processes for enhanced performance.
  1. Weights and Biases Integration:
  • Leverage expertise in the Weights and Biases tool to improve model training, experimentation, and monitoring.
  • Implement and maintain W&B integrations to enhance visibility and collaboration across the ML team.

Qualifications:
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • Proven experience in MLOps, DevOps, and Machine Learning lifecycle management.
  • Strong proficiency with Docker and container orchestration tools.
  • In-depth knowledge of GitHub Actions for CI/CD workflows.
  • Hands-on experience with Amazon SageMaker and AWS services.
  • Familiarity with infrastructure as code (e.g., Terraform).
  • Previous work with Weights and Biases tool.
  • Excellent problem-solving skills and attention to detail.
  • Strong communication and collaboration skills.

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