Applied AI Engineering Intern

About the Role

As an Applied AI Engineering Intern at Instinkt, you will work full-time on-site in Bengaluru. You will collaborate closely with engineers, clinicians, and product teams to help design, implement, and test AI models that process clinical data, generate structured insights, and support physicians in diagnosis and treatment planning.

Key Responsibilities

• Experimenting with machine learning and natural language processing (NLP) techniques.
• Building data pipelines.
• Evaluating model performance.
• Contributing to internal tools and prototypes.
• Translating clinical requirements into technical specifications.
• Documenting work clearly.
• Participating in code reviews and team discussions.

Requirements & Tech Stack

• Foundational knowledge in machine learning and deep learning, including familiarity with supervised and unsupervised learning, evaluation metrics, and model optimization.
• Experience with Python for data science or AI development, using libraries such as NumPy, Pandas, scikit-learn, and at least one deep learning framework (e.g., PyTorch or TensorFlow).
• Skills in data handling and preprocessing, including working with structured and unstructured data, cleaning datasets, and preparing inputs for model training.
• Understanding of natural language processing (NLP) concepts, such as text representation, language models, and information retrieval, or strong interest in learning them.
• Ability to read and interpret technical and clinical documentation.
• Ability to translate requirements into experiments.
• Ability to communicate findings clearly in writing and presentations.

Qualifications

• Currently pursuing or recently completed a degree in Computer Science, Data Science, Engineering, or a related quantitative field.
• Coursework or projects in AI or ML are highly beneficial.
• Comfort working in a collaborative, on-site environment in Bengaluru.
• Openness to feedback, iterative development, and cross-functional teamwork.
• Interest in healthcare and willingness to engage with clinical concepts.
• Prior exposure to health data or medical applications is a plus.