Machine Learning Engineering Intern

Qualification AI RD 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)