Machine Learning Engineer

2 weeks ago


Hyderabad, India Circuitry.ai Full time

Key Responsibilities

  • Develop and optimize machine learning models for structured data, including Regression, SVMs, Decision Trees, Random Forest, and XGBoost.
  • Performing EDA and Feature Engineering
  • Perform Model Fine-Tuning by leveraging techniques like Grid Search and Ensemble Methods .
  • Implement unsupervised learning models such as K-Means and Gaussian Mixture Models .
  • Utilize platforms like AWS SageMaker and tools like MLflow for model training, tracking, and deployment.
  • Train and evaluate machine learning models from scratch using structured data.
  • Work on RNNs and CNNs for structured data tasks as applicable.
  • Leverage libraries like TensorFlow and PyTorch to implement machine learning pipelines.
  • Collaborate with teams to integrate ML models into production systems.
  • Analyze and preprocess large structured datasets to generate insights and drive decision-making.

Qualifications

  • 3+ years of experience in data science with a focus on structured data and machine learning models .
  • Proficiency in Python is a must-have (e.g., NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch).
  • Hands-on experience with machine learning techniques: Regression , SVMs , Decision Trees , Random Forest , and XGBoost .
  • Experience with Feature Engineering techniques, including Grid Search and Ensemble Methods .
  • Familiarity with unsupervised models like K-Means and Gaussian Mixture Models.
  • Strong experience using AWS SageMaker and MLflow for ML workflows.
  • Ability to train and optimize machine learning models from scratch .
  • Solid understanding of machine learning techniques without focus on AI or LLMs.
  • Knowledge of RNN and CNN frameworks for specific tasks.

Nice-to-Have Skills

  • Experience with deployment pipelines for ML models.
  • Familiarity with cloud platforms (e.g., AWS, GCP).
  • Knowledge of SQL for structured data extraction and manipulation.


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