Hello. I am new to Upwork, there is a screenshot attached of my profile.

https://preview.redd.it/5vu66mtlwhzg1.png?width=2374&format=png&auto=webp&s=09491953a1bdfb73dc6685280fe8fc5c451d9dc7

This is not my first experience of working on the project-based tasks but is the first one as a freelancer. What kind of conversion should I expect as an AI Engineer while submitting nice proposals? How can I understand if thats me doing something wrong or thats just part of the game when not everyone responds to my proposals. Are my proposals bad? I give you an example of one of my proposals I submitted:

Developer Needed for Deploying and Optimizing Image Processing Models

Summary

We are seeking a skilled developer to deploy and optimize two open-source models focused on image upscaling and background removal. The primary goal is to enhance the performance for the fastest processing speed and create an API for seamless integration. If you have experience with image processing and optimization, we would love to hear from you. Please provide examples of similar projects you've worked on to ensure a good fit for our requirements.

Proposal:

Cover letter

Hello! My name is Dmytro K. I would like to learn more about your project. What specific models for upscaling and background removal would you like to deploy? In my previous work, I implemented two microservices for image processing: an upscaler using Real-ESRGAN and a background removal service using RMBG models. These services are currently in production at 'some website i cannot mention via subreddit rules' , where I optimized them for low-latency inference through CUDA acceleration, FP16 quantization, and Redis-based task queuing. I'm particularly interested in this project because I've already delivered similar solutions with production-grade reliability. For instance, I built a distributed GPU orchestration system that handles thousands of image processing requests daily while maintaining sub-500ms response times. My experience with FastAPI, Docker, and AWS infrastructure would allow me to deploy your models with robust API endpoints and scalable cloud architecture. I'm confident I can help you achieve both high performance and seamless integration. Looking forward to your response! Best regards, Dmytro K.

• Do you have experience optimzing and running a model on serverless gpu? Need it to be the fastest possible. Yes! In my work for 'some website i cannot mention via subreddit rules' I manage multiple GPU workers and built a Redis-based task queue system for parallel AI inference. The system powers several image-processing services, including background removal, upscaling, image generation, and watermark/text overlay removal. My work includes FastAPI microservices, Dockerized GPU workers, async task processing, model…
• Do you have experience developing an API for it? Yes. I have experience building production APIs around GPU-based AI models. I developed FastAPI-based microservices for multiple image-processing models. The APIs handled request validation, job creation, async task processing through a Redis queue, status tracking, artifact storage, and result delivery. The typical flow I worked with was: Client request -> FastAPI endpoint -> Redis task queue -> GPU worker -> S3-compatible storage -> status/result API. I can build both synchronous APIs for fast inference and asynchronous APIs for heavier GPU jobs where the client submits a task, receives a job ID, polls status, and retrieves the final result once processing is complete.