Machine Learning Intern

🚀 WE'RE HIRING: MACHINE LEARNING (ML) INTERN (100% REMOTE)
Are you passionate about turning complex data into high-impact machine learning models that directly move core business metrics?
At Sowiz (https://www.sowiz.live/), we empower businesses through AI-driven social wisdom and rapid personalized content at scale. We are looking for a high-caliber, mathematically grounded Machine Learning Intern to dive straight into rigorous production-grade R&D for a 6-month duration!
📍 Location: Remote
💼 Duration: Fixed 6 Months
🎯 Target Audience: Recent Graduates (Bachelor's, Master's)
💰 Stipend: Competitive / Industry Standard
🏢 Company: Sowiz (https://www.sowiz.live/)
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💡 WHAT YOU'LL DO:
- Model Development & Iteration: Develop, train, and rigorously iterate on machine learning models tailored for complex forecasting and decision-support use cases.
- Modeling & Architecture: Architect and optimize robust models utilizing strong expertise in tree-based models (CatBoost, XGBoost, LightGBM) alongside deep learning frameworks (PyTorch/TensorFlow).
- Data Engineering & Pipelines: Extract, transform, and manage large-scale datasets leveraging SQL and NoSQL databases to build high-throughput feature engineering pipelines.
- Optimization & Deployment: Apply hyperparameter tuning, model compression, and optimization techniques to maximize inference efficiency.
- Evaluation & Experimentation: Design rigorous validation strategies, analyze error distributions, and track experiments using tools like MLflow or Weights & Biases.
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🎯 WHAT WE'RE LOOKING FOR:
- Education: Recent Graduate (B.Tech, M.Tech, MS) in CS, Statistics, Mathematics, EE, or a related quantitative field.
- Programming Proficiency: Advanced Python programming experience with deep familiarity in NumPy, Pandas, and writing efficient, vectorized code.
- Modeling Expertise: Hands-on implementation experience with tree-based models (CatBoost, XGBoost, LightGBM) as well as neural networks.
- Data Systems: Solid working knowledge of querying and managing data across both SQL and NoSQL databases.
- Core Math Foundation: Strong grasp of linear algebra, multivariable calculus, probability, and optimization theory.
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🌟 TECH STACK & TOOLS:
- Languages: Python (Required), SQL, NoSQL
- Frameworks: CatBoost, XGBoost, LightGBM, Scikit-Learn, PyTorch / TensorFlow, Pandas, NumPy
- MLOps & Tracking: Weights & Biases, MLflow, Git, Docker
- Infrastructure: Linux, AWS/GCP, CUDA
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📩 HOW TO APPLY:
To ensure your application is reviewed:
1. Mail your CV to - [contact shared on WhatsApp] !

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