AI Intern

Company : Soothsayer Analytics

Working Hours : Internship (Full-time)

Locations : Hyderabad

Experience : 0-1 Years

Soothsayer Analytics is a global AI & Data Science consultancy headquartered in Detroit, with a thriving delivery center in Hyderabad. We design and deploy end-to-end custom Machine Learning & GenAI solutions—spanning predictive analytics, optimization, NLP, computer vision, and enterprise AI platforms—that help leading enterprises forecast, automate, and gain a competitive edge.

This internship offers fresh graduates and early-career talent a unique opportunity to learn real-world AI applications and work alongside experienced ML and AI engineers on high-impact projects.

Job Overview

We seek AI Interns who are passionate about AI and machine learning and eager to learn by contributing to applied projects. You will work under the mentorship of senior engineers and data scientists, gaining exposure to data preprocessing, model training, GenAI experimentation, and deployment workflows.

Key Responsibilities

1. Learning & Research

• Explore ML and AI concepts including regression, classification, clustering, and deep learning.
• Experiment with LLMs and GenAI tools such as LangChain and basic RAG concepts.
• Research and prototype small AI and ML projects.

2. Data Preparation

• Assist in cleaning and preprocessing structured and unstructured datasets.
• Support feature engineering and exploratory data analysis.

3. Development Support

• Write basic Python scripts for ML workflows.
• Help in preparing notebooks, documenting experiments, and testing models.

4. Collaboration

• Work closely with mentors and teammates on applied AI tasks.
• Participate in knowledge-sharing sessions and internal hackathons.

Required Skills & Qualifications

• Education: Bachelor’s (final year) or Master’s student in Computer Science, Data Science, AI, or related fields.
• Experience: 0–1 years including academic projects, personal GitHub work, or hackathons.

• Programming: Python (pandas, NumPy, matplotlib)
• ML Basics: Scikit-learn (classification, regression)
• GenAI Exposure: Prompting, basic LLM usage
• Databases: SQL fundamentals
• Version Control: Git basics

Skills Matrix

Instructions for Candidates

• Share your resume highlighting academic, project, or hackathon experience in AI and ML.
• Fill out the above skills matrix honestly (academic exposure counts as experience).
• Share links to GitHub, Kaggle, or personal projects if available.