Description

You will build, deploy, and manage machine learning models and NLP pipelines within an agile environment.

Responsibilities

• Develop machine learning models using regression, XGBoost, random forest, GBM, neural networks, and SVM.
• Implement NLP solutions utilizing RNN, LSTM, and attention-based models, leveraging Stanford, IBM, Azure, and OpenAI models.
• Deploy ML models into production environments using MLOps practices on AWS or Azure.
• Build data applications and visualizations using Streamlit, D3js, and Dash/Plotly.
• Manage codebases and version control via GitHub or Bitbucket.

Required Skills

• 8+ years of experience in data science or machine learning roles.
• Proficiency in Python programming.
• Experience with PySpark and Databricks.
• Deep learning expertise using PyTorch, TensorFlow, and Keras.
• Hands-on experience with AWS AI/ML services including SageMaker, Canvas, and Bedrock.
• Knowledge of computer vision tools such as OpenCV and Pillow/PIL.
• Experience with Flask for model deployment.
• Practical application of predictive modeling and machine learning techniques.
• Experience working within agile project delivery frameworks.

Key Skills

Education

Any Graduate