Intern – AI/ML

Role Overview

Ansrsource is seeking a motivated and talented AI/ML Intern for a full-time hybrid role. This opportunity offers a blend of office collaboration and remote work flexibility. As an AI/ML intern, you will work alongside a team of AI/ML experts, contributing to cutting-edge machine learning projects. Your role will involve analysing data, developing code, troubleshooting, and experimenting with innovative solutions to real-world problems.

Responsibilities

• Assist in developing and deploying machine learning models for various projects.
• Perform data analysis, preprocessing, and feature engineering to prepare datasets for training and evaluation.
• Write clean and efficient code to support ML pipelines and integrate solutions into existing systems.
• Debug, troubleshoot, and optimize code to improve model performance and scalability.
• Explore and implement advanced ML algorithms, including regression, classification, and clustering models.
• Collaborate with cross-functional teams to understand project requirements and deliver solutions.
• Stay updated on emerging trends and tools in AI and machine learning.

Requirements

Education:

• Completed a Bachelor’s or Master’s Degree in Computer Science, Mathematics, or related fields.

Technical Skills:

• Strong foundation in Data Structures, Algorithms, Probability, and Statistics.
• Proficiency in programming languages: Python, HTML, and C++.
• Solid understanding of Machine Learning algorithms, including open-source models, regression, classification, and clustering techniques.
• Experience with TensorFlow, Keras, PyTorch, or other deep learning frameworks is highly desirable.
• Familiarity with Git and understanding of software development principles is a plus.

Good to Have:

• Working knowledge of Transformers, scikit-learn (Sklearn), Pandas, and APIs for building scalable machine learning solutions.

Soft Skills:

• Ability to work independently and collaboratively in a team environment.
• Quick learner with a proactive attitude toward problem-solving and learning new technologies.
• Strong communication skills to articulate ideas effectively within the team and across stakeholders.

Preferred Experience:

• Hands-on experience with real-world datasets and model training.
• Exposure to designing and implementing end-to-end machine learning pipelines.