Machine Learning Engineer

Key Responsibilities:

• Develop and deploy end-to-end microservices-based solutions for batch and real-time ML algorithms

• Build and optimize MLOps pipelines using Kubeflow, Seldon, MLFlow, Docker, and Kubernetes

• Collaborate with Data Scientists to improve ML model development and deployment processes

• Ensure scalability, maintainability, and robustness of ML models in production

• Monitor and troubleshoot ML model performance and infrastructure issues

• Support CI/CD, cloud infrastructure, monitoring, security, and automation processes

• Work with GCP and Azure cloud platforms for deployment and optimization

• Implement logging, monitoring, automated testing, and performance testing

Required Skills:

• 3+ years experience as MLOps Engineer / Machine Learning Engineer

• Strong Python programming skills

• Experience with TensorFlow, PyTorch, scikit-learn

• Strong Kubernetes and Docker experience

• Experience with MLFlow, Kubeflow, and Seldon

• Experience with CI/CD pipelines and automation

• Cloud platform experience, especially GCP and Azure

• Knowledge of ETL, feature engineering, and data processing

• Strong troubleshooting and problem-solving skills