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✔️ TOP RATED Freelancer specializing in Computer Vision and AI-based image processing systems. I enjoy building practical, production-ready solutions for real-world visual problems and would be glad to contribute to your project in a meaningful way. My core focus is on computer vision, especially tasks involving image understanding, detection, and extraction from complex or noisy inputs. I have strong experience working with: ✔️Image Classification & Fine-Grained Recognition (handling subtle visual differences) ✔️Object Detection (YOLO, SSD, Faster R-CNN, TFOD API) ✔️Image Segmentation (Mask R-CNN, semantic & instance segmentation) ✔️OCR & Text Extraction (structured documents, multi-format, noisy images) ✔️Image Preprocessing (denoising, deskewing, perspective correction, enhancement) ✔️OpenCV-based pipelines for real-time and production use ✔️Deep Learning frameworks: TensorFlow, Keras, PyTorch ✔️CNN Architectures: ResNet, VGG, Inception, EfficientNet ✔️Transfer Learning & Custom Model Training ✔️Synthetic Data Generation & Augmentation ✔️Vector Embeddings & Image Similarity Systems ✔️End-to-End CV Pipelines (data collection → training → deployment) Alongside this, I also have a solid foundation in: ✔️Machine Learning & Deep Learning ✔️Mathematics & Statistics (for model understanding and optimization) ✔️Python ecosystem (NumPy, Pandas, SciPy, etc.) ✔️API Development & Deployment(Docker, AWS, GCP) I hold a Bachelor’s degree in Computer Engineering and am currently pursuing a Master’s in AI, which helps me stay aligned with the latest advancements in the field. My approach is always to first understand the business problem and real-world constraints, and then design a solution that is accurate, scalable, and practical to use. I care deeply about delivering solutions that actually work for clients not just in theory, but in real-world conditions. Thanks & Regards, Ruchir

🚀 AI/ML Engineer | Deep Learning | LLMs | FastAPI | Streamlit | RAG Pipelines I’m Aryan Saini, a final-year B.Tech student with 2+ years of hands-on experience building intelligent systems using Python, PyTorch, and modern MLOps tools. I specialize in developing full-stack AI applications—from training custom deep learning models to deploying them via scalable APIs and interactive dashboards. 🔍 What I Can Do for You: • Build and deploy deep learning models (NLP, CV, audio) • Architect RAG pipelines & multi-agent LLM workflows • Integrate HuggingFace, Groq API, OpenAI, and custom fine-tuned models • Develop backend APIs using FastAPI or Express • Create modern UIs with Next.js + Tailwind (Streamlit for quick dashboards) • Deploy on AWS, Vercel, Render, or Docker 🛠️ Key Tools & Frameworks: Python, PyTorch, Transformers, LangChain, FastAPI, Streamlit, Docker, MongoDB, PostgreSQL, OpenAI, Groq, HuggingFace, Tavily, AWS EC2/S3 📌 Highlighted Projects: • ASTRALEARN – AI-powered study planner with LLM agents, RAG search, PDF chatbot • VoxAI – Voice cloning & speech synthesis with TTS/VC models (StyleTTS2, SeedVC) • Multimodal Sentiment Analyzer – Video-based emotion recognition system • Sign Language Recognizer – Real-time gesture classification using CNN + LSTM ✅ Why Hire Me? I’m proactive, fast with iterations, and can take your idea from concept to a fully working AI product. Whether you need help with a proof of concept, research prototype, or a production-grade app, I bring strong technical depth and clean execution. Let’s collaborate to turn your AI vision into reality!

I am an AI/ML developer specializing in Computer Vision, Embedded AI, and real-world automation systems. I work with startups, researchers, and small businesses to design and deploy practical machine learning models that solve real operational problems. With a Bachelor's degree in Computer Engineering (Nanotechnology option) from the University of Alberta, I have hands-on experience with: 1) Object Detection and Face Recognition using OpenCV and YOLO 2) Embedded AI solutions using TensorFlow Lite on Raspberry Pi and Arduino 3) GPT/LLM integration for custom chatbot and PDF summarization tools 4) Automation pipelines using Python, Pandas, Scikit-learn, and Flask 5) Dashboard development with Streamlit and model deployment via APIs I focus on clear code, real results, and business-driven AI—not just academic models. Whether you need help with a one-time project or a long-term collaboration, I deliver production-ready, well-documented solutions with a strong understanding of both software and hardware aspects. Let’s connect if you’re looking for an AI partner who understands systems from edge devices to APIs.

I am an AI engineer with 4 years of experience building and deploying production ready AI systems across computer vision, NLP, and generative AI. I have worked on everything clients need right now: fine tuning and training deep learning models, building RAG and GraphRAG pipelines, LLM powered applications, OCR and document extraction, real time face recognition and multi object tracking, classification systems, embedding pipelines, and end to end data workflows from raw input to deployed output. I also have experience with model optimization including distillation, pruning, and quantization for edge and cloud deployment. On the engineering side I am comfortable with FastAPI, PostgreSQL, pgvector, Python async, and cloud and GPU based deployments. I have built and shipped full stack AI products, not just models. I also lead a team of AI engineers, so I understand both deep technical execution and what it takes to deliver consistently on real projects. If you have an AI problem that needs to actually work in production, I can build it.

I am a Top 3 percent developer on Upwork with the Pink badge, helping clients build native mobile apps that feel smooth, reliable, and truly built for the platform. I build end-to-end AI and machine learning systems that move from research-grade models to production-ready, scalable solutions. My work focuses on combining deep learning, data pipelines, and deployment infrastructure to deliver systems that are accurate, efficient, and reliable in real-world environments. I specialize in designing solutions where models are not isolated components but part of a larger intelligent system architecture. 🔹 Core Expertise Machine Learning & Deep Learning Supervised and unsupervised learning, classification, regression, clustering Deep learning architectures including CNNs, RNNs, Transformers Model optimization, hyperparameter tuning, and performance benchmarking Training pipelines for structured, unstructured, and multimodal data Computer Vision Image classification, object detection, segmentation, and tracking Architectures like YOLO, ResNet, EfficientNet, Vision Transformers Video analytics and real-time inference systems Data augmentation, annotation workflows, and dataset engineering Natural Language Processing Text classification, entity recognition, summarization, and semantic search Transformer-based models like BERT, GPT, and custom fine-tuned models Embedding generation and similarity-based retrieval systems End-to-end NLP pipelines for enterprise use cases 🔹 AI System Engineering I focus heavily on how models behave outside notebooks and inside production systems. Data preprocessing pipelines and feature engineering workflows Batch and real-time inference architectures API-based model serving using FastAPI and Flask Microservices-based AI system design Integration with external systems like CRMs, SaaS platforms, and analytics tools 🔹 Model Deployment & MLOps Model deployment on AWS, GCP, and Azure with scalable infrastructure Containerization using Docker and orchestration using Kubernetes CI/CD pipelines for automated training, testing, and deployment Model versioning, monitoring, and performance tracking Handling concept drift, retraining strategies, and lifecycle management 🔹 What I Build Computer vision systems for detection, tracking, and visual intelligence NLP systems for document processing, search, and conversational understanding End-to-end ML pipelines from data ingestion to model deployment Real-time AI systems with low latency and high throughput AI-powered applications integrated into web and mobile platforms 🔹 My Approach I treat every project as a production system from day one. Focus on scalability, reliability, and maintainability Design for edge cases and noisy real-world data Balance model accuracy with latency and cost constraints Build modular pipelines that can evolve over time 🔹 Differentiation Strong combination of deep learning expertise and engineering execution Experience handling real-world data challenges like imbalance, noise, and scale Ability to convert research ideas into deployable systems End-to-end ownership from data to deployment 🔹 Tech Stack Python, TensorFlow, PyTorch, OpenCV, Scikit-learn, Hugging Face, FastAPI, Flask, Docker, Kubernetes, AWS, GCP, Azure If you are looking to build robust AI systems, not just models, I can help you design, develop, and deploy solutions that work reliably at scale. Let us build intelligent systems that perform beyond the lab.

I am an AI/ML engineer with 3+ years building production machine-learning systems, backed by a research track record: two accepted peer-reviewed papers, a two-time Google Summer of Code contributor, and published GPU work. What I can build for you: • LLM & vision-language fine-tuning — QLoRA/PEFT, dataset creation, evaluation, deployment-ready inference. • Self-hosted & open-source LLM deployment — running models on your own GPU servers for privacy, control, and lower cost. • RAG systems & AI agents — retrieval grounded in your documents, data, and tools, with evaluation and monitoring so it stays reliable in production, not just in a demo. • GPU & scientific computing — CUDA/CuPy/JAX acceleration, profiling, and pipelines that process terabytes of data • Full-stack delivery — FastAPI backends, React/Electron front-ends, Docker/Kubernetes, so the model ships as a real product your team can run How I work: define the use case, build the smallest reliable version first, test the edge cases, document everything, and hand you code your team can maintain after the contract ends. Core stack: Python, PyTorch, Hugging Face, CUDA/CuPy, FastAPI, React, Docker, Kubernetes. I am Top Rated with 100% Job Success and I reply within a few hours. Tell me what you're trying to build and I will build it for you.