Infrastructure Engineer (part time) with ML Experience for US Restaurant Operation Startup

About the company

• Be part of US ML startup with high growth potential.
• Work on cutting-edge AI solutions impacting the restaurant and food supply chain industry.
• Gain experience in real-world ML deployment, cloud-based AI systems, and full-stack development.
• Potential equity-based compensation and long-term involvement as we scale.

Job Role

• Integrate models with iOS applications (Swift) and web platforms (React, JavaScript, CSS).
• Develop deep learning models for natural language processing (NLP), named entity recognition (NER), and information extraction from menus.
• Build demand forecasting models using time-series techniques (ARIMA, DeepAR, Prophet, Transformer/LSTMs).
• Work on GraphML and graph databases (Neo4J) to enhance supply chain analytics.
• Develop and deploy machine learning models into cloud-based environments (GCP, Firebase, Cloud Functions, Cloud Storage, Cloud Compute).
• Design and implement web-based ML dashboards to visualize food inventory and demand trends.
• Develop APIs and microservices in Python and JavaScript for seamless backend integration.
• Connect the ML platform to POS systems (Square, Toast) to streamline restaurant operations.

Requirements

• Experience with deep learning for NLP and time-series forecasting.
• Background in graph databases and GraphML (preferred).
• Must HAVE experience with GCP
• Proficiency in React, Swift, and cross-platform development
• Interest in food supply chain management, restaurant tech, and predictive analytics.
• Comfortable working in a fast-paced startup with evolving priorities.

Tech Stack

• ML/AI: Deep Learning (NER, NLP), Time-Series Forecasting (ARIMA, LSTMs, Prophet, DeepAR), Large Language Models (LLMs).
• Databases: Neo4J (GraphDB), Cloud Storage Solutions.
• Cloud: Google Cloud Platform (GCP), Firebase, Cloud Functions, Cloud Compute.
• Frontend: React (Web), Swift (iOS).
• Backend: Python, JavaScript (Microservices).