MLOps Engineer

This is a remote position.

• Build and automate ML pipelines for training, deployment, monitoring, and retraining.
  
• Deploy and manage machine learning solutions on cloud platforms, preferably Azure.
  
• Implement model monitoring, governance, versioning, and performance tracking.
  
• Collaborate with Data Science and Engineering teams to productionize ML models.
  
• Manage cloud-based ML services and infrastructure.
  
• Improve MLOps platforms, tools, and deployment practices.
  
• Work with stakeholders and technology partners to deliver scalable ML solutions.
  

Requirements

• 5-8 years of experience in ML Engineering, MLOps, or related roles.
  
• Strong hands-on experience with Python.
  
• Experience with TensorFlow, PyTorch, or Scikit-learn.
  
• Strong understanding of the ML lifecycle and model deployment.
  
• Experience with cloud platforms such as Azure, AWS, or GCP.
  
• Experience building automated CI/CD and ML pipelines.
  
• Knowledge of Docker, Kubernetes, MLflow, or Kubeflow.
  
• Strong communication and stakeholder management skills.
  

Benefits

• Competitive compensation and benefits.
  
• Remote and flexible work environment.
  
• Opportunity to shape technology strategy and business outcomes.
  
• Strong learning and leadership growth opportunities.