AI / Backend / Computer Vision Engineer — Fitness App, Digital Twin & AI Coach

FIDI is an AI-native fitness transformation system combining health data, body photos, measurements, workouts, nutrition, computer vision, digital twin generation, and adaptive AI coaching. We are looking for an AI/backend/computer vision engineer to build the intelligence layer, backend services, data model, and AI workflows that power the app. Responsibilities The engineer will be responsible for: Backend API architecture User accounts and authentication Snapshot data model Health data ingestion model Photo and measurement storage Workout data model Nutrition data model AI coach orchestration Computer vision workflows Body capture quality scoring Food recognition pipeline Gym equipment recognition pipeline Progress projection engine Transformation recommendation logic AI-generated workout and nutrition guidance Data privacy, deletion, and export systems Cloud storage and deployment infrastructure Required Experience The ideal candidate has experience with: Python and/or TypeScript Backend API development PostgreSQL or similar relational databases Cloud storage AI API integration LLM orchestration Computer vision Image processing Pose detection Fitness, health, sports science, nutrition, or wearable data Secure handling of user data Scalable backend architecture Strong Advantage Experience with any of the following is highly preferred: OpenAI API or similar LLM systems Realtime AI voice or chat systems Structured AI outputs RAG / retrieval systems MediaPipe Apple Vision / Core ML TensorFlow / PyTorch Food recognition models Human pose estimation Body measurement estimation 3D model or digital twin pipelines HealthKit / Health Connect backend data structures Fitness recommendation engines Deliverables The engineer will deliver: Backend API Database schema AI coach service Snapshot processing pipeline Health data ingestion model Computer vision quality scoring Food scan processing workflow Gym equipment scan workflow Progress projection logic Workout and nutrition recommendation logic Admin/debug tooling where needed Cloud deployment setup Security and privacy documentation Technical handoff documentation Key Product Areas The engineer must be able to support: Body capture analysis Digital twin generation workflow AI coach memory and context Workout recommendations Nutrition recommendations Progress projections Gym equipment recognition Food recognition Health data interpretation Privacy-first handling of sensitive fitness and body data Reporting The engineer reports directly to the founder or appointed technical lead. The role is delivery-focused. Product strategy, final product decisions, roadmap priority, and acceptance criteria remain with the founder. Ownership All code, models, prompts, workflows, datasets, architecture, documentation, and technical work produced under this role are work-for-hire and become the property of the company/project. No equity, founder rights, product ownership, or strategic control is attached to this role unless separately agreed in writing.