Machine Learning Engineering Intern
Full-time Unpaid Collaboration Internship
01
Available Positions
Fresher's having BE (IT/CS/CE), BSc.(IT/CS,CE), BCA, MCA, MBA (IT/CS/CE)
Experience
Bachelor's degree in Computer Science, AI/ML, Data Science, or related field (final year students or recent graduates)
Qualification
AI R&D
Department
Role Overview
Join our ML engineering team to explore cutting-edge machine learning technologies, develop scalable AI solutions, and contribute to real-world applications. This collaborative learning opportunity focuses on end-to-end ML pipeline development, model deployment, and production system optimization.
Key Responsibilities
- Design, develop, and optimize machine learning models using Python, TensorFlow, PyTorch, and scikit-learn frameworks
- Build and maintain robust ML pipelines from data preprocessing through model deployment and monitoring
- Conduct data analysis, feature engineering, and statistical validation to ensure high-quality model performance
- Implement model evaluation frameworks and A/B testing infrastructure for continuous improvement
- Collaborate with cross-functional teams including data scientists, software engineers, and product managers
- Deploy ML models to production environments using Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure)
- Participate in code reviews, technical discussions, and contribute to research publications when applicable
Required Qualifications
Must-Haves
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or related field (final year students or recent graduates)
- Strong programming proficiency in Python with experience in NumPy, Pandas, and machine learning libraries
- Solid understanding of machine learning algorithms including supervised/unsupervised learning, neural networks, and deep learning
- Knowledge of data structures, algorithms, and software engineering best practices
- Experience with version control systems (Git) and collaborative development workflows
Nice-to-Haves
- Hands-on experience with deep learning frameworks like TensorFlow, PyTorch, or Keras
- Familiarity with MLOps practices, model deployment, and production monitoring systems
- Understanding of computer vision, natural language processing, or reinforcement learning applications
- Experience with cloud-based ML services and containerization technologies
- Previous internship experience or significant open-source contributions in ML/AI projects
Learning Outcomes and Development
- Gain hands-on experience with end-to-end ML system development from research to production deployment
- Master industry-standard ML engineering tools, frameworks, and methodologies through mentorship from senior engineers
- Develop expertise in scalable ML infrastructure, model optimization, and performance monitoring techniques
- Build comprehensive understanding of real-world ML challenges including data quality, bias evaluation, and system reliability
- Access to cutting-edge research projects with potential for academic publications and conference presentations
- Enhanced collaboration skills through cross-functional team projects and regular technical presentations
This unpaid internship represents a collaborative knowledge-sharing opportunity in the rapidly expanding field of machine learning engineering. Outstanding performers will be considered for full-time positions based on technical excellence, problem-solving abilities, and demonstrated impact on ML system development.
Duration: 6 months
Hours: 09:00 AM to 06:00 PM (Monday to Friday)
Location: Ganesh Glory 11, Jagatpur, Ahmedabad, 382470 (Offline Internship)