Senior Machine Learning Engineer

4 weeks ago

Islamabad, Islamabad, Pakistan Confiz Full time

We are looking for a Machine Learning Engineer with 2-4 years of experience to develop and optimize ML pipelines, perform exploratory data analysis (EDA), feature engineering, and build scalable data preparation modules. The ideal candidate should have strong expertise in Python, Spark, PySpark, and Spark Delta, along with knowledge of traditional machine learning techniques.

Responsibilities:

  1. Conduct exploratory data analysis (EDA) to uncover insights and patterns in datasets.
  2. Apply statistical analysis and traditional machine learning techniques (regression, classification, clustering, etc.).
  3. Develop and optimize scalable data preparation and feature engineering pipelines.
  4. Work with Spark, PySpark, and Spark Delta to process large-scale datasets efficiently.
  5. Implement and optimize ML models for production use cases.
  6. Collaborate with data engineers and data scientists to integrate models into business applications.
  7. Tune ML model performance using appropriate evaluation metrics and hyperparameter optimization.
  8. Ensure efficient data processing and storage using Spark and distributed computing frameworks.
  9. Stay up to date with the latest advancements in ML engineering, big data processing, and cloud technologies.

Requirements:

  1. Bachelors or equivalent Degree in Computer Science, Information Technology or related field.
  2. 2-4 years of experience in machine learning engineering, data science, or big data processing.
  3. Strong programming skills in Python or R for data analysis and ML development.
  4. Hands-on experience with Spark, PySpark, and Spark Delta for distributed data processing.
  5. Hands-on experience in Python scientific computing ecosystem (pandas, numpy, scikit-learn, matplotlib, XGBoost, LightGBM etc).
  6. Proficiency in traditional machine learning techniques and statistical analysis.
  7. Experience with data preprocessing, feature engineering, and model training.
  8. Familiarity with SQL and big data platforms for data extraction and transformation.
  9. Understanding of model deployment and optimization for scalability.
  10. Strong analytical and problem-solving skills with a keen attention to detail.

Preferred Qualifications:

  1. Experience working with cloud-based ML platforms (Azure ML, AWS SageMaker, Google Vertex AI).
  2. Exposure to MLOps practices, CI/CD pipelines for ML models.
  3. Knowledge of deep learning frameworks (TensorFlow, PyTorch) is a plus.
  4. Experience working with streaming data and real-time ML pipelines.
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