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
- ML Models
- Python
- TensorFlow
- PyTorch
Preferred Technologies
- ML Models
- Python
- TensorFlow
- PyTorch
Benefits
- Early-stage equity
- Competitive salary
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