The Role We're looking for an ML Engineer to build and own the intelligence layer. You'll work across food recognition, recommendation systems, and conversational AI to create a product that genuinely improves user's health outcomes.
What You'll Build
Food recognition pipeline using computer Vision models API and custom models fine-tuned on firms datasets
Recommendation engine combining collaborative filtering and content-based filtering (nutrients, ingredients, textures)
Pattern detection using time-series models (LSTM/Prophet) to identify nutritional deficiencies and preference shifts early
RAG-based chat system grounded in verified pediatric nutrition guidelines using llms
Voice transcription pipeline using OpenAI Whisper, aws transcribe and likes for hands-free logging
Requirements
3+ years building and shipping ML models in production
Strong Python skills — TensorFlow, PyTorch, scikit-learn
Experience with recommendation systems or time-series modeling
Familiarity with LLMs and RAG architectures
Comfortable working with APIs (Google Vision, OpenAI, USDA FoodData Central)
Nice to Have
Experience in health, nutrition, or pediatric applications
Experience fine-tuning vision models on domain-specific datasets
What We Offer
Early-stage equity — meaningful ownership in a growing consumer AI company
Remote-first, async-friendly culture
Direct impact on product — you own the ML roadmap
Competitive salary based on experience
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