Job Title

As aDeep Learning Engineer Intern , you'll dive into our core ML stack, working alongside our senior engineers on Computer Vision, Recommendation Systems, and LLM‑based Features (optional). You'll get hands‑on with real data, tackle edge‑case challenges, and iterate rapidly on prototypes that power our food‑robotic machine.Team Structure:You'll be joining a focused 2-person full-time ML team as our 1st intern, reporting directly to Lead. Small team size means significant mentorship and direct impact on product development.Growth Opportunity:Strong potential for full-time conversion based on performance - we're actively looking to grow our ML team with exceptional talent.What You'll Work OnIngredient Segmentation, Recipe Similarity, Vision-Language Models Package and deploy models for on‑device inference and AWS services Support data collection and annotation; refine datasets based on model performance across scenarios Iterate on experiments—tune hyper parameters, test augmentations, and document resultsWhat We're Looking ForStrong fundamentals in Deep Learning (Transformers, CNNs) and classical ML (Logistic / Linear regression) Hands‑on experience with PyTorch (academic projects, internships, or personal work) Comfortable coding in Python and using the broader ML ecosystem (NumPy, pandas) Solid understanding of training pipelines, evaluation metrics, and experimental rigour Eagerness to learn new domains (NLP, recommendations) and iterate quicklyBonus (Nice to Have) Prior exposure to LLMs or multi‑modal models Experience with computer vision in challenging real-world environments (lighting, occlusion, texture variations) Projects on noisy, real‑world datasets or edge‑case‑heavy scenarios♀️ Why You'll Love It HereEarly ownership:contribute end‑to‑end to ML features, not just isolated components Work withreal robotic systemsin homes—see your models live in action solving ingredient recognition and recipe understanding Close mentorship:Direct access to senior ML engineers in a small, focused team environment Rapid feedback loops: prototype, deploy, and learn within days Clear growth path:Strong potential for full-time conversion into a rapidly expanding ML teamWho You AreCurrently enrolled in a B.Tech or M.Tech program (3–4 years into your degree) Strong math & ML fundamentals—beyond just using off‑the‑shelf libraries Thrives in an ambiguous, fast‑paced startup environment Always curious—loves building, experimenting, and sharing insightsOther details : Location:Bangalore (4 days WFO & 1 day WFH) Duration:3–6 month internship Compensation:₹1,00,000/month Education:Currently pursuing B.Tech / M.Tech (IISc, IITs, IIITs, NITs, or BITS Pilani)How to Apply Applications without a project portfolio will not be considered. Please include the following in your resume: GitHub profile showcasing ML/deep‑learning projects Public codebase from coursework, internships, or personal work Kaggle notebooks or competition solutions with leaderboard standings