MLOps Engineer
Summary
Shuru Technologies is hiring a remote MLOps Engineer to build and automate ML pipelines and manage scalable machine learning infrastructure on cloud platforms (Azure preferred). Day to day involves model deployment, monitoring, versioning, and retraining, working with data scientists using Python, Docker, Kubernetes, and MLflow/Kubeflow.
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.