Machine Learning Engineer / Data Scientist

About the Role 

We are looking for a skilled and motivated Machine Learning Engineer / Data Scientist
to join our team. The ideal candidate should have a strong foundation in machine 
learning and deep learning, with experience in building end-to-end ML pipelines and 
hybrid modeling approaches that incorporate both physics-based simulations and 
data-driven insights. You will work on high-impact projects involving time series 
forecasting, predictive modeling, and system simulation to support data-driven 
decision-making. 
 
Key Responsibilities 

 Design, train, and evaluate machine learning and deep learning models for 
regression, classification, and forecasting tasks. 
 Build and maintain end-to-end ML pipelines, including data ingestion, 
preprocessing, feature engineering, model training, validation, and deployment. 
 Develop physics-informed or hybrid models by combining domain knowledge 
with machine learning approaches to simulate and predict system behaviors. 
 Implement and optimize time series forecasting models using statistical 
techniques, classical ML, and deep learning architectures (e.g., LSTM, 
Transformer). 
 Collaborate with cross-functional teams to translate business needs into 
machine learning solutions. 
 Monitor and refine model performance post-deployment to ensure robust, 
scalable outcomes. 

Key Skills Required 

 Strong knowledge of Machine Learning and Deep Learning algorithms and their 
applications. 
 Proven experience in building and deploying end-to-end ML pipelines. 
 Hands-on experience in physics-based modeling or hybrid approaches 
combining physical models with data-driven techniques. 
 Solid understanding of time series forecasting using statistical (ARIMA, ETS), 
machine learning (XGBoost, RF), and deep learning (RNN, LSTM, Temporal CNN) 
methods. 
 Experience designing regression and classification models for real-world 
problems. 
 Proficiency in Python, and libraries like TensorFlow / PyTorch, scikit-learn, 
pandas, NumPy, statsmodels, etc. 
 Strong problem-solving mindset and ability to work with minimal supervision.