ML Engineers/Data Scientists-Well Known IT Co.@ Techno Park-Trivandrum

2 weeks ago

Thiruvananthapuram, Kerala, India Sperton Full time ₹ 5,00,000 - ₹ 15,00,000 per year

Role Overview;-

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.

Role & 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.

Preferred Candidate Profile:-

  • 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 (XG Boost, 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 Tensor Flow / Py Torch, scikit-learn, pandas, NumPy, stats models, etc.
  • Strong problem-solving mindset and ability to work with minimal supervision.

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