AI Engineer for Small Business Assistant System

@Microlent

Hello, I am an experienced AI Engineer with over 3+ years specializing in building and deploying Large Language Models (LLMs) and advanced NLP solutions for multi-lingual, real-world applications. Key Expertise: Proficient in Python with strong AI/ML engineering skills, including training, fine-tuning, and deploying LLM-based systems. Experienced in developing and optimizing NLP pipelines for both voice and text processing in English and Hindi. Skilled in integrating AI models with backend systems (Node.js) and managing conversational data using MongoDB. Familiarity with speech processing technologies such as ASR (speech-to-text) and TTS (text-to-speech) for seamless local and offline AI interaction. Strong foundation in data science fundamentals including data preprocessing, model evaluation, and performance benchmarking. I’m excited to contribute to creating an intelligent, multi-lingual AI assistant that drives impactful business solutions. Best regards, Vicky Keswani

@CodeniaTechno

Hello infoaios, We are Codenia Technologies LLP, with over 10 years of experience in PHP, Android, and Mobile App Development. We have carefully reviewed your project requirements for an AI Engineer for the Small Business Assistant System. Our approach involves designing, training, and deploying Large Language Models (LLMs) for multi-lingual environments, optimizing NLP pipelines for voice and text processing, integrating AI models with backend systems, and collaborating with speech processing teams. We are keen to discuss your project further and explore how we can contribute to its success. We would like to connect with you in a chat to delve deeper into the specifics of your project. Thanks, Rupesh Kumar

@KarthikTechCon

Hi, I’m Karthik, a seasoned AI/ML engineer with 10+ years of experience building intelligent systems for businesses. I specialize in LLM-based solutions, NLP pipelines, and speech processing, making me well-suited to develop your AI Assistant System for Small Businesses with multi-language support (English + Hindi). What I Offer: LLM Development: Design, train, fine-tune, and deploy large language models optimized for local execution. NLP & Speech Integration: Build pipelines for voice and text understanding, integrating ASR/TTS for natural interactions. Backend Integration: Connect AI models with your backend using Node.js and MongoDB for real-time responses and conversation storage. Optimization & Benchmarking: Ensure offline-capable AI execution, efficient performance, and continuous improvement. Deployment & Scalability: Deliver production-ready solutions tailored for small business environments. Why Me: Strong Python expertise with practical AI/ML engineering experience. Proven track record in deploying LLMs and AI assistants for real-world applications. Experience in speech-to-text, text-to-speech, and multi-lingual NLP. I’m confident I can help you build a robust, intelligent, and scalable AI assistant that enhances customer interactions. I’m ready to start immediately and provide a full technical solution. — Karthik

@abdf2010

Hello, I liked your project AI Engineer for Small Business Assistant System, which aligns perfectly with my professional expertise. I bring extensive experience in PHP, Python, Mobile App Development, I can ensure timely delivery within 3 days. I'm committed to exceeding your expectations and would welcome the opportunity to discuss your requirements in detail.

@webskittersIT

Webskitters LLC is a national award-winning company recognized for its web development, design, and digital marketing excellence. With 3,000+ successful projects and 7+ years of expertise, Webskitters LLC transforms your vision into a high-impact digital reality. Trusted by global brands, built for results. Hi, I will build and deploy your multilingual AI assistant system (LLM fine-tuning, NLP pipelines, ASR/TTS integration) to support both speech and text in English and Hindi, with real-time backend integration and MongoDB-based conversational storage. My method: I will fine-tune compact LLMs for bilingual comprehension, create robust NLP pipelines for intent and entity recognition, integrate Whisper/ASR and Coqui TTS for low-latency voice interactions, implement real-time APIs with Node.js, optimize models for local/offline inference, and set up monitoring, benchmarking, and CI/CD for consistent performance and improvements. Tech stack: Python, PyTorch, Hugging Face Transformers Whisper or Vosk for ASR; Coqui/TTS for speech synthesis Node.js for real-time API integration MongoDB for conversational storage and retrieval Docker, ONNX/quantization for local/offline deployment Prometheus/Grafana for performance monitoring I’m ready to start building your production-grade, multilingual AI assistant—let’s finalize milestones so I can deliver a secure, low-latency solution quickly. Best regards, Atanu.S

@digitrixsoftware

Hi, I’m ready to help you build a real-world AI Assistant for small businesses—one that comprehends both voice and text in English and Hindi, runs efficiently offline, and offers seamless backend integration for intelligent call handling. What I’ll Do Design, fine-tune, and deploy LLM-based models for multi-lingual voice and text interactions. Build robust NLP pipelines to preprocess input from speech (ASR) and interface output (TTS). Deploy lightweight, offline-capable inference, optimized for local performance. Integrate models with your backend (Node.js + MongoDB) for real-time conversational flow. Support the speech team (ASR/TTS), benchmark model performance, and iterate continuously. Why Choose Me 2+ years of hands-on LLM development, fine-tuning, and deployment in Python. Solid experience in multi-lingual NLP and efficient inference setups. Familiar with backend integrations (Node.js, MongoDB) and building systems with real-time, low-latency requirements. Next step: Let’s sync on your current stack, preferred LLM (e.g. Llama2, OpenAI), and performance targets. I can then send a one-page technical approach with milestones for your review. Best regards, Bhavik Patel