Machne Learning Intern

Company Description Vaani builds AI voice agents designed specifically for healthcare settings, helping providers improve patient communication, reduce administrative workload, and streamline care delivery. The company focuses on creating reliable, secure, and accessible voice technologies that integrate with existing healthcare workflows. Team members work at the intersection of machine learning, speech technology, and healthcare operations to solve practical, high-impact problems. Vaani offers opportunities to contribute to solutions that can improve patient experiences and support healthcare professionals in their daily work.
Role Description This is a full-time, on-site Machine Learning Intern role based in Kolkata. The intern will support the design, development, and evaluation of machine learning models for AI voice agents, including data preprocessing, feature engineering, and model training. Day-to-day tasks may include working with speech and text datasets, implementing and testing algorithms, running experiments, analyzing performance metrics, and documenting findings. The role involves close collaboration with engineers and product team members to refine models for real-world healthcare use cases and improve system accuracy, robustness, and scalability. The intern is expected to participate in code reviews, contribute to prototype development, and continuously learn new tools and techniques relevant to machine learning and AI in healthcare.
Qualifications
Strong foundation in machine learning, statistics, and applied mathematics, with familiarity in supervised and unsupervised learning methods.
Programming skills in languages commonly used for ML (such as Python) and experience with ML libraries or frameworks (for example, TensorFlow, PyTorch, or scikit-learn).
Experience working with data pipelines, including data cleaning, preprocessing, and handling structured and unstructured data (such as text or audio).
Understanding of natural language processing or speech-related concepts is beneficial, including text processing, embeddings, or basic ASR concepts.
Ability to design experiments, evaluate models using appropriate metrics, and clearly communicate results and trade-offs to technical and non-technical stakeholders.
Strong problem-solving skills, attention to detail, and ability to learn quickly in a fast-paced, collaborative environment.
Current enrollment in or recent completion of a degree program in Computer Science, Data Science, Engineering, or a related quantitative field.
Interest in healthcare technology and ethical, responsible AI; prior exposure to healthcare datasets or workflows is a plus.

Work arrangement
No