Data Engineer
2 weeks ago
We are seeking an experienced AI/ML expert to develop a cutting-edge, custom analytical engine that will integrate as an add-on to our existing platform. This engine will enable advanced data analysis, predictive modelling, and other AI-driven functionalities that enhance the user experience and drive decision-making. The ideal candidate will have proven experience in machine learning, data science, and AI, and a deep understanding of developing robust, scalable systems that integrate seamlessly with our existing platforms.
Role & responsibilities
- Design & Develop AI/ML Model: Build a comprehensive engine capable of performing advanced data analysis, predictive analytics, and real-time insights. This will include developing machine learning models, algorithms, and data processing pipelines.
 - Data Analysis & Modelling: You will be required to conduct thorough analysis of available datasets, create training datasets, and implement appropriate ML algorithms to address specific business requirements (e.g., classification, regression, clustering, anomaly detection, etc.). This will more so apply to our specific domain of analysing Pumping stations and Pump-sets.
 - Optimization & Performance Tuning: Optimize the performance and efficiency of the developed AI/ML models, ensuring they can handle large volumes of data and deliver real-time analytics.
 - Testing & Validation: You will need to perform rigorous testing and validation of models and algorithms to ensure accuracy, robustness, and reliability.
 - Documentation & Knowledge Sharing: This will be most important aspect of your engagement. You will be required to provide detailed documentation of the solution, including design decisions, architecture, and usage guidelines. In addition, you may Share insights and strategies for maintaining and evolving the system
 
Preferred candidate profile
- Proven expertise in Machine Learning, Deep Learning, and AI techniques.
 - Strong proficiency in Python, R, or other relevant programming languages commonly used in AI/ML development.
 - Solid understanding of various AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn, etc.).
 - Experience working with big data tools and technologies (e.g., Spark, Hadoop) is a plus.
 - Expertise in data pre-processing, feature engineering, and model training techniques.
 - Familiarity with cloud computing platforms (e.g., AWS, GCP, Azure) for deploying AI models at scale.
 - Ability to translate complex AI/ML concepts into actionable business solutions.
 - Strong problem-solving skills, attention to detail, and the ability to work independently.
 
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