AST-2026-002 AI Voice Assistant for Parking Customers AI Developer 07 PFE

Project Summary

• Develop an AI-powered voice assistant to provide instant support to parking customers for common issues (lost tickets, payment errors, gate malfunctions).
• Leverage Natural Language Processing (NLP) to enable automated, human-like voice interactions that improve customer experience and reduce manual support workload.

Objectives & Deliverables

• Produce a working prototype that can understand voice queries and respond appropriately for the specified parking use cases.
• Deliverables include: trained NLU models, dialogue flows, FastAPI backend endpoints, integration examples with Dialogflow or Rasa, and a demonstration script for typical customer scenarios.

Technical Tasks & Responsibilities

• Design and implement NLU pipelines using TensorFlow or PyTorch for intent classification and entity extraction.
• Build conversational logic with LangChain (or equivalent) and create dialogue management for multi-turn interactions.
• Integrate voice input/output using Dialogflow or Rasa voice connectors and implement backend services with FastAPI to interface with parking systems (ticket/payment/gate APIs).
• Implement logging, metrics and basic evaluation (accuracy, intent F1, dialogue success rate) and iterate on models based on evaluation results.

Technologies & Architecture

• Expected technologies: Python, TensorFlow or PyTorch, LangChain, Dialogflow or Rasa, FastAPI.
• Architect the solution to allow modular model updates, REST API endpoints for conversational state, and connectors to external parking/payment systems.

Candidate Profile

• Required: strong skills in Python and familiarity with NLP/ML frameworks (TensorFlow or PyTorch).
• Preferred: experience with conversational frameworks (Dialogflow or Rasa), LangChain or similar for chaining prompts, and backend API development with FastAPI.
• Good to have: experience with speech-to-text / text-to-speech integrations, familiarity with telephony/voIP connectors, and practical evaluation/monitoring of conversational agents.

How to apply

• Or send your application email to careers@asteroidea.co with the subject "Application AST-2026-002 - AI Voice Assistant for Parking Customers PFE".
• Include CV, short cover letter, and links to relevant projects or GitHub repositories demonstrating NLP or conversational AI work.