Freelancers using FastAPI in Paris

Freelancers using FastAPI in ParisFreelancers using FastAPI in Paris

Projects People

Sathwika Bandaru

Saint-Denis, France

AI Engineer building LLM, RAG & AI automation solutions

New to Contra

AI Engineer building LLM, RAG & AI automation solutions

Cover image for Collaborative project, contributed key production

Collaborative project, contributed key production components of Med-V²QA, a clinical Visual Question Answering system built on the MUMC architecture for radiology image analysis. My contributions: built the Dual-Gate Guardrail System (Gate 1 rejects non-medical intent, Gate 2 uses a local CLIP classifier to reject non-medical images ensuring clinical safety and system focus); developed the Batch Triage module using zero-shot CLIP to automatically sort and prioritise the most abnormal scans from uploads of up to 20 images; integrated Voice I/O using OpenAI Whisper for speech-to-text transcription and gTTS for audio readout of answers; built the PDF report generation module producing structured clinical reports with patient data, notes, and VQA results; and developed the FastAPI backend handling high-performance async request processing across all services. Built as part of a team my work covered the safety layer, multimodal I/O, clinical reporting, and backend API infrastructure.

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Cover image for Built a Medical NLP system

Built a Medical NLP system that processes clinical text to extract healthcare entities, redact sensitive information, and structure unstructured medical data using NER pipelines and FastAPI for backend integration.

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Cover image for Collaborative project built at Kaggle

Collaborative project built at Kaggle Week 26 GenAI Hackathon, contributed the core AI engineering layers of a Business Law RAG Assistant that answers legal document queries with source citations and live faithfulness verification. My contributions: built the hybrid FAISS + BM25 retrieval pipeline for accurate document search; designed the multi-agent orchestration system coordinating retrieval, generation, and verification agents; implemented the faithfulness verification layer to evaluate and score LLM output quality; integrated an MCP tool server enabling live web search as a fallback; and built the analytics dashboard tracking query performance and retrieval metrics. Built as part of a 4-person team, my work covered the RAG pipeline, agentic architecture, and evaluation infrastructure.

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Cover image for Built as part of a

Built as part of a team, my contributions covered the pipeline orchestration, model serving, and data infrastructure layers.

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AI / Cloud Solution Architect, driving innovation

AI / Cloud Solution Architect, driving innovation

Cover image for Electronic Document Management (EDM) AI Application

Electronic Document Management (EDM) AI Application

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Cover image for Project Summary: MongoDB Monitoring with Prometheus & Grafana

Project Summary: MongoDB Monitoring with Prometheus & Grafana

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Cover image for News Aggregator with Custom Content Processing

News Aggregator with Custom Content Processing

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Ismail ait-lahssen

Building AI-Powered Workflows & Business Systems

New to Contra

Building AI-Powered Workflows & Business Systems

Cover image for Production-oriented ML system built with

Production-oriented ML system built with a modular architecture separating data processing, feature engineering, inference, API services, persistence, and training pipelines for scalable and maintainable deployment workflows.

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Cover image for Production-oriented credit risk ML system

Production-oriented credit risk ML system with reproducible training, saved artifacts, automated tests, and CLI-based inference workflows.

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Cover image for Production-oriented credit risk ML system

Production-oriented credit risk ML system with reproducible training, saved artifacts, automated tests, and CLI-based inference workflows.

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Cover image for Developed a production-oriented ML repository

Developed a production-oriented ML repository with modular source architecture, automated testing, CI workflows, inference APIs, and structured engineering documentation following real-world software development practices.

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