- We are looking for a hands on MLOps Engineer who will work closely with Data Scientists and ML Engineers to build deploy monitor and optimize machine learning models in production
- This role is NOT focused on platform engineering or infrastructure only work instead it emphasizes end to end ML lifecycle management model deployment and operationalization of ML systems
- Strong Python programming
- Hands on experience in Machine Learning workflows
- Experience with MLOps tools
- MLflow Kubeflow Airflow SageMaker Vertex AI
- Knowledge of CI CD tools GitHub Actions Jenkins etc
- Experience deploying models using
- Docker REST APIs Flask FastAPI
- Understanding of
- Model versioning
- Experiment tracking
- Model monitoring
- Exposure to cloud platforms AWS Azure GCP for ML deployment
- Knowledge of LLMOps GenAI deployment pipelines
- Familiarity with
- Feature stores
- Data pipelines Spark Kafka
- Experience with Kubernetes basic deployment level
- Experience with real time inference systems
- Exposure to monitoring tools Prometheus Grafana
- Knowledge of LLM deployment RAG pipelines
Analytics->Data Science,Technology->Machine learning->data science,Technology->Machine Learning->Generative AI
