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We are looking for a 3D GenAI Engineer / AI 3D Pipeline Developer It is necessary to create a solution that can qualitatively generate 3D models from a single image or multiple images. It is important that this is not just a ready-made demo, but a clear and reproducible process: from the input image to a full-fledged 3D asset with mesh, geometry, textures, and the possibility of further use. What needs to be done: - test modern image-to-3D models and approaches; - determine which option is best suited for our task; - use Trellis, Hunyuan3D, or similar solutions; - if necessary, use Gaussian Splatting in the 3D pipeline; - configure the conversion of Gaussian Splat / splat representation into 3D mesh; - obtain usable geometry; - generate high-quality textures; - bring the result to a usable 3D asset state; - find the optimal balance between quality, generation speed, and pipeline complexity; - build a clear process that can be repeated for different images; - perform fine-tuning, LoRA, or other model adaptations for specific types of objects.

About the Project We are looking for an experienced AI Automation Engineer to design and build a secure, self-hosted AI platform that combines a local Large Language Model (LLM), Retrieval-Augmented Generation (RAG), and multiple AI agents to automate business workflows. This is a hands-on engineering role for someone who has experience building production AI systems—not simply integrating ChatGPT APIs. The goal is to create a private AI ecosystem capable of securely indexing company knowledge, answering questions using cited sources, processing meeting transcripts, and automating internal business processes. Responsibilities You will be responsible for: Designing and deploying a locally hosted LLM on a VPS or dedicated server Building a secure RAG pipeline using frameworks such as LlamaIndex or similar Creating document ingestion pipelines supporting PDF (including OCR), DOCX, TXT, XLSX and meeting transcripts Implementing document indexing, metadata management, deduplication, and versioning Developing AI agents for: Meeting transcription processing Automatic meeting summaries Action item extraction Client knowledge retrieval Building APIs or a simple web interface for querying the knowledge base Ensuring strict client data isolation and permission controls Implementing source-cited responses to minimize hallucinations Optimizing system performance, scalability, and reliability Writing documentation and deployment guides Performing testing and security validation Required Skills Strong Python development experience Experience with LLM frameworks RAG architecture experience LlamaIndex, LangChain, or equivalent Vector databases (Qdrant, Chroma, Pinecone, Weaviate, FAISS, etc.) Local/open-source LLM deployment (Llama, Mistral, Gemma, DeepSeek, etc.) API development (FastAPI preferred) Docker Linux server administration VPS deployment Git Authentication and access control Experience with OCR pipelines Experience working with structured and unstructured documents Fluent English What We’re Looking For The ideal candidate: Has built production AI systems from the ground up Understands RAG best practices Can work independently Thinks like a software architect—not only a developer Writes clean, maintainable code Communicates clearly Can recommend the best technologies instead of simply following instructions Project Type Freelance / Contract Remote Milestone-based Long-term opportunity for future AI automation projects Please Include With Your Application Portfolio of similar AI/RAG projects Examples of local LLM or AI agent implementations Estimated timeline Estimated project cost Hourly or fixed-rate pricing

There is a Telegram bot on aiogram/FastAPI (CRM for an event project) and a separate ManyChat bot in Instagram Direct for communication with clients.Task 1 — fix the logic of the Instagram Direct bot.The current bot is made according to a strict script: it works step by step (greeting → about the event → response to "too expensive" → response to "I'll think about it"), with 3 random text options for each step. The problem is that the bot does not understand the meaning of the message, but guesses the step number and sends a template that is off-topic. Because of this: when asked directly about the price, the bot does not provide numbers but sends general text the language jumps — sometimes Ukrainian, sometimes Russian essentially, it is a randomizer of templates, not a dialogueIn a week, the bot lost several live leads. I can provide screenshots of conversations as examples.Need: for the bot to actually analyze the content of the message (question about price, objection "too expensive", doubts "I'll think about it", non-standard question, etc.) and respond appropriately — based on AI (for example, Claude API), not according to a strict script. The tone should be lively, not robotic, and the language should be Ukrainian. Basic scenarios (price, discounts, handling "too expensive"/"I'll think about it") need to be preserved, but the AI should choose the appropriate response based on the context.Task 2 (optional, but also needed) — auto-posting in Instagram.Posting through the official Meta Graph API: reels, stories, posts, carousels. Tags in the bot: [reels] / [stories] / [post] / [carousel] + [geo] / [poll] / [countdown]. Multi-user panel /admin — adding/removing people, roles (posting / viewing / all), activity log. Dynamic price from Google Sheets — the bot pulls the current price from the "Price" column.Questions for the performer: Is it better to implement Task 1 (AI logic for Instagram Direct) on top of the current ManyChat via webhook + external AI processor, or as a separate bot on an architecture like aiogram/FastAPI, connected to Instagram through the official Meta API? Are you taking on both tasks together (Direct logic + auto-posting)? What is the total cost and timeframe for the entire scope (task 1 + task 2)?Requirements: Experience with Meta Graph API (Instagram) Experience integrating AI models (Claude API / OpenAI API) into chatbots Preferably — experience with aiogram/FastAPI or ManyChat webhooks Portfolio with similar projects

Project Title: Automation of content publication on social media via a Telegram bot using AI Task Description: Our company sells premium fitness equipment from the Italian manufacturer Panatta in Ukraine. We manage several social media platforms: Instagram, Facebook, TikTok, and a Telegram channel. An automated solution needs to be developed that will allow us to quickly adapt and publish video content across all our social media platforms. Main Logic of Operation: I send a link to a video from YouTube, Instagram, or TikTok to the Telegram bot. The system automatically retrieves the description of this video, translates it into Ukrainian, adapts the text to the live communication style of the Panatta brand, adds links to our social media, and publishes the finished post on: Instagram, Facebook, TikTok, Telegram channel. Important: The video itself does not need to be changed or translated. We need to work with the video description: translation, adaptation, text optimization, and publication together with the video or a link to it — depending on the technical capabilities of the specific platform. Desired Workflow Scenario: I send a link to the video to the Telegram bot. The system identifies the source: YouTube, Instagram, or TikTok. The system retrieves the original video description. AI translates the description into Ukrainian. AI adapts the text to the premium brand style of Panatta: professionally, lively, without dry machine translation. Links to our social media are automatically added to the text: Instagram, Facebook, TikTok, Telegram. The system prepares the publication for each platform. The publication is automatically posted on Facebook, Instagram, TikTok, and the Telegram channel. It is preferable to have the option to review the text and confirm publication via the Telegram bot before posting. Desired Functionality of the Telegram Bot: The bot should accept links to videos. The bot should display the generated Ukrainian text before publication. It is preferable to add buttons: "Publish", "Edit", "Generate Again", "Cancel". The bot should notify whether the post was successfully published on each social media platform. It is preferable to keep a history of processed links. Possible Technical Stack: We are considering various implementation options: Make.com, n8n, Zapier, custom backend, Telegram Bot API, OpenAI API, or other AI services. We are open to contractor suggestions regarding the optimal technical solution. Additional Considerations: It is necessary to check the technical limitations of the APIs for Instagram, Facebook, TikTok, and YouTube. A stable account authorization scheme needs to be proposed. It should be explained whether fully automatic publication is possible on all social media or if manual confirmation is required for some platforms. Protection against post duplication should be anticipated. The solution should be made as simple as possible for daily use. Expected Result: A working automation system where a link to a video can be sent via the Telegram bot, an adapted Ukrainian description can be received, and content can be published on Facebook, Instagram, TikTok, and the Telegram channel. What is required from the contractor in the response: Briefly describe how you propose to implement this solution. What stack will you use: Make.com, n8n, custom development, or another option. Which social media can be fully automated, and where might there be limitations. Estimated implementation timelines. Estimated cost. Examples of similar automations, if any. Additional Information: The Panatta brand represents premium Italian sports equipment for fitness clubs. Therefore, the texts must not only be translated but also adapted to the Ukrainian market, with the correct positioning: premium quality, Made in Italy, biomechanics, design, professional level of equipment. Links to our social media will be provided to the selected contractor.

Automation is needed for sending messages with a link to the KP on LinkedIn, WhatsApp, Reddit. Please describe how this will be implemented, the timeline, and the cost.