AIOps Engineer

The core requirements for the job include the following:
ML/DL Engineering:
Strong understanding of Machine Learning algorithms including Classification, Regression, Clustering, Time-Series Forecasting, Predictive Analytics, and Anomaly Detection.
Experience in Deep Learning LSTM models using frameworks TensorFlow and PyTorch for predictive analytics and time-series forecasting.
Strong knowledge of Feature Engineering, Statistical Modelling, Model Evaluation, and Explainable AI (SHAP/LIME).
ML Operations:
Strong proficiency in Pandas, Scikit-learn, PySpark, NumPy, TensorFlow, PyTorch, FastAPI/Flask, and REST API development.
Experience with MLOps using Kubeflow/MLflow, Docker, Kubernetes, ML model deployment, model monitoring, CI/CD, and ML lifecycle management.
Model performance optimisation using Hyperparameter Tuning.
Consulting and Delivery:
Strong customer communication, solution consulting, requirement gathering, presentation, and stakeholder management skills.
Experience delivering enterprise AI solutions from PoC through production deployment.

Experience
3-7 yrs