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Machine Learning Engineer

Xpressbees (BusyBees Logistics Solutions Pvt. Ltd.)

Location

Remote

Salary

Not specified

Type

fulltime

Posted

Today

via linkedin

Job Description

We are looking for a skilled Machine Learning Engineer / Predictive Modelling Specialist who can design and build predictive models from scratch and work with large-scale datasets. The ideal candidate should have strong expertise in machine learning algorithms, statistical modelling, and scalable data processing, with the ability to translate business problems into data-driven solutions.

Key Responsibilities:

  • Design, develop, and deploy predictive models and machine learning solutions for complex business problems.
  • Build end-to-end ML pipelines including data preprocessing, feature engineering, model training, validation, and deployment.
  • Work with large-scale structured and unstructured datasets to derive insights and develop modelling features.
  • Develop models from scratch using statistical and machine learning techniques.
  • Optimize model performance through feature engineering, experimentation, and hyperparameter tuning.
  • Collaborate with data engineering teams to support scalable data pipelines and model deployment.
  • Monitor model performance and ensure reliability in production environments.

Required Skills \& Experience :

  • Having 6-8yrs of strong experience in Predictive Modelling and Machine Learning.
  • Hands-on experience building ML models from scratch.
  • Experience handling large datasets and high-volume data processing.
  • Strong programming skills in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) and SQL.
  • Solid understanding of statistics, model evaluation, and feature engineering.
  • Exposure to distributed data processing tools (e.g., Spark) and MLOps/model deployment concepts is a plus.

Preferred Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or related fields.
  • Experience with cloud platforms (AWS, GCP, Azure) or large-scale data platforms.
  • Exposure to AI applications, advanced analytics, or deep learning frameworks.

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