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MLOps Engineer

$125k

Inizio Partners

MLOps Engineer

Dallas, Texas, United States

$ 125,000.00 - 125,000.00 (US Dollar)

Job Title: MLOps Engineer

Job Description:

We are seeking a highly skilled and experienced MLOps Engineer to join our client. As an MLOps Engineer, you will play a crucial role in developing and implementing machine learning operations processes and infrastructure to support our data science initiatives.

Responsibilities:

  • Develop and maintain end-to-end machine learning operations (MLOps) pipelines for deploying, monitoring, and scaling machine learning models.
  • Collaborate with data scientists, software engineers, and DevOps teams to ensure seamless integration of ML models into production systems.
  • Design and implement automated testing frameworks for ML models to ensure accuracy, reliability, and performance.
  • Optimize model deployment processes by leveraging containerization technologies such as Docker or Kubernetes.
  • Implement continuous integration/continuous deployment (CI/CD) practices for ML model development lifecycle management.
  • Monitor deployed ML models in production environments to identify performance issues or anomalies.
  • Work closely with cross-functional teams to troubleshoot issues related to model performance or data quality in production systems.
  • Stay up-to-date with the latest advancements in MLOps toolkits, frameworks, best practices, and industry trends.

Requirements:

  • Bachelors degree in computer science or a related field; advanced degree preferred.
  • Minimum 5 years of experience working as an MLOps Engineer or similar role within a data-driven organization.
  • Experience with Kubernetes and Kubeflow is mandatory.
  • Strong understanding of machine learning concepts and algorithms.
  • Proficiency in Python developing ML pipelines/scripts.
  • Experience with popular MLOps toolkits such as Kubeflow Pipelines, TensorFlow Extended (TFX), MLflow, etc., is essential.
  • Solid knowledge of containerization technologies like Docker and Kubernetes for deploying ML models at scale.
  • Familiarity with cloud platforms like AWS/Azure/GCP for building scalable infrastructure solutions is highly desirable
  • Experience with version control systems like Git/GitHub for managing code repositories
  • Excellent problem-solving skills with the ability to analyze complex technical issues related to ML model deployments.

Location:

Remote/Dallas.

Package Details:

  • Base - $125,000
  • Bonus - 15% - 18%
  • Full Benefits
Vacancy posted 2 days ago
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