Summary:
Responsible for deploying, monitoring, and maintaining machine learning models in production. Ensures the reliability, scalability, and performance of AI/ML pipelines.
Key Responsibilities:
- Design and implement CI/CD pipelines for ML workflows.
- Manage model versioning, testing, and deployment.
- Monitor model performance and retrain as needed.
- Optimize infrastructure for cost and speed.
- Collaborate with data scientists, engineers, and DevOps teams.
Required Skills:
- Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
- Experience with cloud platforms (AWS, Azure, GCP).
- Knowledge of containerization (Docker, Kubernetes).
- Familiarity with MLOps tools (MLflow, Kubeflow, SageMaker).
- Strong understanding of data pipelines and APIs.
Experience:
3–5 years in machine learning or DevOps, with MLOps experience preferred.
Job Type: Contract
Work Location: Remote
