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Deccan AI

ML Intern

Posted 10 Days Ago
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In-Office
Mountain View, CA, USA
Internship
In-Office
Mountain View, CA, USA
Internship
As a Machine Learning Intern, you'll design, train, and evaluate ML models, work on data preprocessing, develop pipelines, and assist with model deployment while collaborating with experienced engineers.
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About Us

Deccan AI is a model training and eval startup headquartered in the Bay Area. We are founded by IIT Bombay, IIM Ahmedabad and ex-Google alumni, and work with some of the top AI frontier labs in the world, e.g. Google Deepmind, Snowflake, and many more. We are backed by Prosus Ventures, and our India delivery office is in Hyderabad. Most of our roles are on-site i.e. Bay Area / Hyderabad.
About the Role

We’re looking for a Machine Learning Intern who’s eager to dive into real-world AI challenges — from model experimentation to data pipelines and evaluation. You’ll work closely with our ML and product teams, contributing to projects that combine research thinking with hands-on engineering.

This role is ideal for someone who loves building, experimenting, and learning fast.

What You’ll Do
  • Support in designing, training, and evaluating ML models across different problem areas.

  • Work on data preprocessing, feature engineering, and annotation workflows.

  • Assist in building scripts, pipelines, and dashboards for model performance tracking.

  • Collaborate with senior engineers on model fine-tuning and deployment experiments.

  • Stay updated on the latest AI papers, tools, and frameworks, and bring fresh ideas to the team.

What You’ll Bring
  • Pursuing or recently completed a degree in Computer Science, AI, Data Science, or related fields.

  • Strong foundation in Python and experience with PyTorch / TensorFlow / Scikit-learn.

  • Understanding of core ML concepts — supervised/unsupervised learning, metrics, data splits, etc.

  • Familiarity with data analysis tools (Pandas, NumPy) and visualization (Matplotlib, Seaborn).

  • Curiosity to explore new ML techniques and the ability to work independently in a fast-paced setup.

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