ML Engineer
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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
- scikit-learn
- APIs
Preferred Technologies
- ML models
- Python
- TensorFlow
- PyTorch
- scikit-learn
- APIs
Benefits
- Early-stage equity
- Remote-first culture
- Competitive salary
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