Description

You will design, develop, and deploy machine learning models and deep learning architectures.

This role is on-site.

Responsibilities

• Implement machine learning algorithms, NLP, and computer vision techniques.
• Handle data preprocessing and feature engineering to prepare datasets for modeling.
• Manage the end-to-end model lifecycle including training, evaluation, and deployment.
• Utilize MLOps tools to automate and scale machine learning workflows.

Required Skills

• 5+ years of experience in machine learning or related engineering roles.
• Proficiency in Python, specifically using NumPy, Pandas, and Scikit-learn.
• Hands-on experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Experience with MLOps tools including MLflow, Kubeflow, or SageMaker.
• Knowledge of cloud-based AI services such as AWS SageMaker, Azure ML, or GCP AI.
• Strong understanding of ML algorithms and model deployment strategies.
• Bachelor's degree or equivalent graduate-level education.

Preferred Skills

• Experience managing production-level ML pipelines within cloud environments.

Key Skills

Education

Any Gradute