SportsBUZZ
Website:
sportsbuzz.com
Job details:
Machine Learning Intern (Paid)
Company: SPORTSBUZZ
Location: Remote
Duration: 3 Months
Stipend: Performance-based up to ₹7,500 - ₹15,000
Employment Opportunity: Potential full-time role based on performance + Certificate of Internship
📅 Application Deadline: 26th February 2026
About SPORTSBUZZ
SPORTSBUZZ offers students and graduates hands-on learning opportunities in Machine Learning and Data Science. The internship focuses on practical exposure to real-world projects, enabling interns to build strong technical foundations and gain industry-relevant experience in AI and analytics.
Role Overview
As a Machine Learning Intern at SPORTSBUZZ, you will work on live projects involving data analysis, model development, and algorithm design. This role is designed to strengthen your understanding of machine learning concepts while helping you build a professional, portfolio-ready skill set.
Key Responsibilities
- Design, test, and optimize machine learning models
- Clean, preprocess, and analyze datasets for modeling
- Develop algorithms and predictive models for real-world applications
- Work with tools such as TensorFlow, PyTorch, and Scikit-learn
- Document findings and prepare reports to communicate insights clearly
- Collaborate with mentors and team members to improve model performance
Eligibility & Requirements
- Currently enrolled in or recently graduated from AI, Machine Learning, Data Science, Computer Science, or related fields
- Strong understanding of machine learning concepts and algorithms
- Proficiency in Python or R (preferred)
- Strong analytical, problem-solving, and teamwork skills
Perks & Benefits
- Performance-based stipend up to ₹7,500-₹15,000
- Swags and goodies
- Certificate of Internship upon successful completion
- Letter of Recommendation based on performance
- Opportunity for a full-time role based on performance
Equal Opportunity for All
SPORTSBUZZ is committed to fostering a diverse and inclusive workplace and encourages applicants from all backgrounds to apply.
Click on Apply to know more.