Deep Learning Engineering Intern

As a Deep Learning Engineer Intern, you will have the opportunity to work on our core ML stack, focusing on areas such as Computer Vision, Recommendation Systems, and LLM-based Features (optional). Working closely with our senior engineers, you will gain hands-on experience with real data, address edge-case challenges, and rapidly iterate on prototypes that drive our food-robotic machine. You will be an integral part of a focused 2-person full-time ML team, serving as our first intern and reporting directly to the Lead. This small team size ensures significant mentorship opportunities and allows you to make a direct impact on product development. Your responsibilities will include: - Working on tasks such as Ingredient Segmentation, Recipe Similarity, and Vision-Language Models - Packaging and deploying models for on-device inference and AWS services - Supporting data collection and annotation, refining datasets based on model performance - Iterating on experiments, tuning hyperparameters, testing augmentations, and documenting results We are looking for candidates with: - Strong fundamentals in Deep Learning (Transformers, CNNs) and classical ML (Logistic / Linear regression) - Hands-on experience with PyTorch in academic projects, internships, or personal work - Proficiency in Python and the broader ML ecosystem (NumPy, pandas) - Solid understanding of training pipelines, evaluation metrics, and experimental rigor - Eagerness to learn new domains such as NLP and recommendations Nice to have skills include prior exposure to LLMs or multimodal models, experience with computer vision in challenging real-world environments, and projects involving noisy, real-world datasets or edge-case-heavy scenarios. Working with us, you will enjoy: - Early ownership of ML features, contributing end-to-end to projects - Hands-on experience with real robotic systems in homes, witnessing your models in action - Direct access to senior ML engineers for mentorship in a small, focused team environment - Rapid feedback loops that allow you to prototype, deploy, and learn quickly - A clear growth path with strong potential for full-time conversion into our rapidly expanding ML team We are looking for candidates who are currently enrolled in a B.Tech or M.Tech program (3-4 years into their degree), possess strong math and ML fundamentals beyond using off-the-shelf libraries, thrive in an ambiguous, fast-paced startup environment, and are always curious, enjoying building, experimenting, and sharing insights. Location: Bangalore (4 days WFO & 1 day WFH) Duration: 3-6 month internship Compensation: 1,00,000/month To apply, ensure your resume includes a project portfolio with the following: - GitHub profile showcasing ML/deep learning projects - Public codebase from coursework, internships, or personal work - Kaggle notebooks or competition solutions with leaderboard standings,