About the role
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.