Machine Learning Engineer – Industrial AI Applications

7 days ago

Remote, India Einnosys Technologies LLP Full time ₹ 35,000 - ₹ 15,00,000 per year

We are seeking a skilled and innovative Machine Learning Engineer with experience in building predictive models for real-world industrial applications, including manufacturing, turbine failure detection, and laser machining. You will be responsible for developing machine learning solutions that improve system reliability, process efficiency, and product quality.

Key Responsibilities

  • Analyze sensor data and simulation/experimental datasets to build machine learning models for system failure prediction and maintenance.
  • Develop and optimize regression and classification models (e.g., XGBoost, Random Forest, Gradient Boosting, Neural Networks).
  • Apply feature engineering and data preprocessing techniques to prepare complex datasets for modeling.
  • Evaluate model performance using metrics like recall, accuracy, AUC-ROC, R², MAE, etc.
  • Collaborate with domain experts (mechanical, materials, or manufacturing engineers) to interpret data and model results.
  • Work on use-cases like:
  • Turbine failure/shutdown prediction.
  • Metal additive manufacturing quality and geometry prediction.
  • Optimization of laser machining parameters using ML.
  • Document model development and provide actionable insights based on model outcomes.
  • Deploy and integrate models into existing data pipelines (optional, based on project).

Required Skills & Qualifications

  • Bachelor's or Master's degree in Computer Science, Data Science, Mechanical/Manufacturing Engineering, or a related field.
  • Strong programming skills in Python (pandas, scikit-learn, XGBoost, TensorFlow/PyTorch, etc.).
  • Experience with classification and regression models.
  • Understanding of metrics like R², MAE, precision/recall, and AUC-ROC.
  • Solid foundation in machine learning algorithms and data preprocessing techniques.
  • Experience working with engineering or sensor data is a big plus.
  • Ability to collaborate with cross-functional teams and explain technical findings to non-technical stakeholders.

Preferred Qualifications

  • Experience with industrial or manufacturing datasets (sensor, simulation, or experimental data).
  • Background or interest in materials science, additive manufacturing, or mechanical systems.
  • Familiarity with neural networks and deep learning architectures.
  • Experience in optimization and model tuning for high-performance metrics.

Job Type: Full-time

Pay: ₹350, ₹1,500,000.00 per year

Application Question(s):

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Work Location: Remote

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