About the job
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
Requirements
- Python
- TensorFlow
- PyTorch
- scikit-learn
- NLP
- Time-series modeling
Preferred Technologies
- Python
- TensorFlow
- PyTorch
- scikit-learn
- NLP
- Time-series modeling
Benefits
- Equity
- Remote-first culture
About the company
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