Hire the Best PyTorch Professionals

I help researchers, startups, and businesses turn AI ideas into working MVPs and scalable products through machine learning development, AI model integration, AI/Backend Engineer, Workflow Automations and research-backed implementation & writing support. 🏆 Top Rated | 100% Job Success | about $10K+ Earned | 40+ Completed Upwork Jobs Whether you need to validate an AI idea, integrate an existing model, reproduce research code, or improve an ML pipeline, I can help move your project from concept to a reliable implementation. 🏆 MVPs to Scalable Products | AI Research & Development | Research Support-Asistance 🧠 Deep Learning | Machine Learning | ML Model Training & Fine-Tuning | APIs | LLMs 🌟 2D/3D Vision | Sensors and Medical Data | GitHub & Hugging Face Code Reproduction 🧠 Classification, Regression, Time Series, Forecasting, Detection & Recognition WHAT I CAN HELP YOU BUILD: ✅ AI & Machine Learning MVPs, SaaS, Startup Predictive models, prototypes, backend APIs, AI model integration, and deployment-ready workflows. ✅ Deep Learning & Computer Vision Solutions Image classification, object detection, segmentation, anomaly detection, medical imaging, and 2D/3D vision pipelines. ✅ LLM, RAG & AI Integration OpenAI API integration, LangChain workflows, ChromaDB knowledge bases, retrieval pipelines, and AI-powered applications. ✅ Model Training & Fine-Tuning Data preparation, training pipelines, experimentation, evaluation, optimization, and reproducible implementation. ✅ Research Support & Code Reproduction Research-paper implementation, GitHub and Hugging Face code reproduction, benchmarking, ablation studies, experiment support, and technical reporting. ✅ Medical & Scientific Data Solutions Research-focused machine learning workflows for structured, image, and multimodal datasets. ✅ Time-Series & Sensor Data Solutions Forecasting, anomaly detection, signal processing, predictive modelling, and machine learning workflows for sensor, IoT, and sequential datasets. CORE TOOLS: Python | PyTorch | TensorFlow/Keras | Scikit-learn | OpenCV | Vercel AI | Github | Hugging Face | Flask | FastAPI | OpenAI API | Claude Code | LangChain | ChromaDB | Next.js | SQL | Docker | R/Rstudio | Matlab PyTorch | TensorFlow | Deep Learning | Neural Networks | Machine Learning | Machine Learning Model | Large Language Model | RAG | AI Model Development | AI Model Integration | Data Engineering | biostatistics | Statistical Analysis | Data Engineering | Image processing | Signal Processing WHAT YOU CAN EXPECT ✓ Clear communication and realistic scoping ✓ Clean, reproducible code and documentation ✓ Research-backed implementation decisions ✓ Flexible collaboration across USA, Europe, UK, and Australia time zones I also support Python/R Data Science Data Analysis, NLP, LLMs, OpenAI API, RAG chatbots, Clinical Data, Data Engineering, scraping tasks projects and build ETL pipelines as well as setup databases. Share your idea, dataset, existing codebase, or research paper, and I will help define the most practical path from prototype to implementation.

✅ $300K+ Earned | Top Rated Plus | 8,000+ Hours | 38 Jobs | 100% Job Success I build production-grade LLM, RAG, and AI Agent systems. Not prototypes. Not API wrappers. Real Python pipelines, deployed on AWS, handling real traffic. If your AI needs to actually work in production, let's talk. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🤖 LLM AND GENERATIVE AI ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ End-to-end LLM applications using OpenAI (GPT-4o), Claude, Gemini, LLaMA, and Mistral. Full RAG pipelines over your documents, databases, and knowledge bases. AI Agents and multi-agent workflows built on LangChain, LangGraph, and LlamaIndex. LLM fine-tuning with LoRA, QLoRA, PEFT, RLHF, and DPO on open-source models. Prompt engineering, tool calling, memory patterns, guardrails, tracing, and LLM evaluation harnesses. If your team is moving an LLM prototype to production, this is exactly where I work. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚡ FASTAPI AND DJANGO BACKENDS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ FastAPI and Django are my backend stack of choice for AI-powered services. → Async REST APIs: FastAPI + Pydantic + SQLAlchemy + PostgreSQL → Scalable Django backends: DRF, Celery, Redis, multi-tenant SaaS architecture → FastAPI as the serving layer for LangChain, RAG, and agent endpoints → Auth systems: JWT, OAuth2, RBAC → Microservices, Docker, Kubernetes, CI/CD via GitHub Actions and GitLab CI → Swagger / OpenAPI documentation, clean architecture, full test coverage ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎙️ VOICE, AUDIO, VIDEO AND TEXT AI ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ → Voice AI agents and real-time speech pipelines (Whisper, AssemblyAI, Deepgram, ElevenLabs, VAPI, Retell AI) → STT / TTS integration, NLP, NER, and multimodal LLM pipelines → Computer Vision: YOLO, OpenCV, CNNs, Vision Transformers → Diffusion pipelines and image / video generation workflows → Audio transcription, classification, and processing at scale ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🧠 ML, MLOPS AND VECTOR SEARCH ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ML Stack: PyTorch, TensorFlow, HuggingFace, scikit-learn, XGBoost Vector DBs: Pinecone, Weaviate, Milvus, FAISS, pgvector, Elasticsearch Serving: vLLM, TGI-style inference, batching, caching, routing, streaming responses MLOps: MLflow, DVC, Prefect, Ray, eval harnesses, regression testing, tracing Cloud: AWS (SageMaker, EKS, EC2, Lambda, Bedrock, DynamoDB, CloudFront), Terraform, GPU providers ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🏆 WHAT MAKES ME DIFFERENT ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Most AI freelancers deliver a Jupyter notebook or a thin wrapper around an API. I architect and ship the full system. I have 14+ years of engineering experience and a background as a Fractional CTO and AI/ML Team Lead. I have led teams and personally written the code. I think in systems, delivery, and cost control, not just individual features. At Alethea AI, I was part of the team that built a cloud-native architecture on AWS capable of accommodating 30 million visitors, highlighted in an official AWS case study. The platform publicly closed a $16M token sale. That is the level of production reliability I bring to every engagement. ✔ Architecture designed for scale from day one ✔ Clean code, full documentation, and production observability ✔ I write the code myself, no offshoring your project ✔ Reliable delivery: timelines, milestones, and accountability ✔ Cost-controlled cloud and GPU workloads ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🤝 WHO I WORK WITH ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Startups validating AI-first MVPs fast. Scaleups moving LLM prototypes to production. Product teams that need a senior AI/ML engineer who can own the full stack, from fine-tuned model to FastAPI endpoint to deployed AWS service. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📩 Message me with your current state, timeline, and constraints. If I can help, I will tell you exactly how, usually within a few hours.

I’m an AI/ML Engineer with a strong background in Python, TensorFlow, and PyTorch, and hands-on experience in delivering real-world machine learning solutions. I specialize in Deep Learning, Computer Vision, and Natural Language Processing, and I’ve built and deployed models across various domains: Selected Projects: Hieroglyphics Symbol Recognition (Siamese Network) Built a deep learning model using Siamese architecture + InceptionV3 to compare and classify hieroglyphic symbols. Achieved 83% accuracy and deployed interactive demos. Speech Emotion Recognition System Developed an SER pipeline using CNNs, AssemblyAI, and OpenAI APIs. Achieved 75.58% accuracy in emotion detection from speech signals. Dental X-ray Tooth Segmentation (U-Net GAN) Applied U-Net GAN to segment teeth from dental X-rays. Achieved high accuracy despite limited data. Gait Analysis with IMU Sensors Built ML models to detect abnormal gait patterns using IMU sensor data, including a full data visualization dashboard. Custom Object Detection (YOLO) Trained a YOLO model on custom datasets and evaluated it using mean Average Precision (mAP) metrics. Facial Emotion Detection (CNN) Created a CNN-based classifier to detect facial expressions using image datasets. English–French Machine Translation (Transformer) Fine-tuned a MarianMT transformer model and evaluated translations using BLEU scores. Cat Face Generator (GAN) Designed a Deep Convolutional GAN (DCGAN) to generate realistic images of cat faces from scratch. Skills & Tech Stack: Languages: Python, SQL, Java, C++, C#, Go Libraries: TensorFlow, Keras, PyTorch, OpenCV, scikit-learn Tools: Google Colab, Jupyter, Git, Linux Bonus Skills: Data Augmentation, Model Explainability (SHAP, LIME), TensorFlow Lite I’m fast-learning, detail-oriented, and passionate about building AI solutions that create real value. Let’s collaborate and turn your idea into a smart, production-ready ML product.

Are you looking to bridge the gap between cutting-edge AI research and a production-ready software application? I am a Software Engineer specializing in Machine Learning, Computer Vision (CV), and Full-Stack Development. Over the last 2+ years, I have helped a fast-paced US startup and global clients design, train, and deploy high-performance deep learning models and robust APIs. 🚀 Core Strengths & How I Can Help Your Business Custom Computer Vision & Deep Learning: Designing and optimizing models for action segmentation, video alignment, and robotic manipulation using PyTorch. Scalable API Development: Building high-speed, production-ready backend APIs using FastAPI and Flask to seamlessly serve AI models. Full-Stack Integration: Integrating complex machine learning pipelines into user-friendly applications using the MERN Stack (React, Node.js, Express). Model Optimization: Tuning architectures to squeeze out maximum performance—recently achieving up to 15.3% IoU and 15.1% F1 improvements in complex CV tasks. 🏆 Key Accomplishments & Education Published AI Researcher: My contributions to novel deep learning methods are published in top-tier computer vision venues, including ICCV 2025 and WACV 2026. US Startup Experience: Proven track record of working closely with cross-functional teams and international clients to deliver clean, maintainable code in fast-paced environments. Academic Foundation: Bachelor of Science (BS) in Computer Science, grounding my practical development skills in strong computer science fundamentals.

AI Agents | Python | Data Science | LLM Integration | RAG Pipelines | Recommendation Engines | MLOps | API Integration | n8n & langchain Automation I am an AI Engineer and Data Scientist with 5+ years of experience building production-grade machine learning systems that directly move business metrics. I help scaling businesses and enterprises replace manual bottlenecks with automated AI infrastructure, intelligent recommendation systems, and autonomous agents. You don't just need a script; you need a system that doesn't break. I take projects from zero data to live inference and self-healing pipelines. WHAT I BUILD (Proven Enterprise & Agency Use-Cases): • AI Agents & Social Automation: Built "Instafarm" – an enterprise-grade, cloud-phone automated fleet utilizing LLMs and n8n to execute high-volume, human-like outreach and reputation management at scale. • Recommendation Engines (ZOOP & Global Retail): Built a system from scratch for a US social media startup (10k+ MAU) and a top-15 global grocery retailer (100K+ SKUs), increasing engagement and recipe-to-cart conversion. • LLM & RAG Pipelines: Engineered LLM-powered content generation for Raiffeisen Bank, ensuring strict tone-of-voice alignment, advanced prompt engineering, and context window management. • CMS & CRM Automation: Created ML pipelines for a restaurant media platform that replaced months of manual data entry with automated classification and Human-in-the-Loop workflows for 4,000+ listings. WHY CLIENTS HIRE ME: • Beyond "Wrapper" Tech: Unlike freelancers who only know how to connect basic API blocks, I am a Data Scientist. I build custom architectures, dense retrieval pipelines, and secure cloud infrastructure. • Enterprise Reliability: I build systems trusted by global banks and top retailers. • End-to-End Ownership: From data preprocessing and feature engineering to AWS deployment (Terraform) and MLOps. TOOLS & TECH STACK: AI & LLMs: OpenAI, Claude, Gemini, LangChain, LangGraph, Hugging Face, Multi-Agent Systems, RAG, Prompt Engineering, CLIP, Sentence-BERT. Automation & Integrations: n8n, Make, Zapier, API Development, FastAPI. Data Science & ML: Python, PyTorch, TensorFlow, scikit-learn, XGBoost, FAISS, OpenSearch, Vector Databases. Cloud & DevOps: AWS (SageMaker, Kinesis, Lambda, S3, DynamoDB), Docker, PostgreSQL, Terraform. If you want an AI system built with the right architecture, scalable, secure, and revenue-focused send me an invite and let's talk.

Data Annotation Specialist | Image, Video & Audio Labeling I provide accurate, consistent data annotation for machine learning projects. You get clean, well-structured datasets ready for training and evaluation. I work with images, videos, and audio across different domains. I follow strict labeling guidelines and deliver on time. 🚀 Experience - I have supported projects that required: - Image annotation for object detection and classification - Video annotation with bounding boxes and tracking - Keypoint labeling for pose and object parts - OCR text transcription and region labeling - Audio transcription and tagging I understand how high-quality data improves model accuracy. 📌 Annotation Types - Bounding boxes - Polygons and segmentation masks - Keypoints and landmarks - Classification labels - Object tracking across frames - OCR text labeling Audio transcription and labeling ⚙️ Tools - CVAT - LabelImg - LabelMe - Roboflow - Supervisely - Custom annotation tools if needed 💡 How I Work - Follow your labeling guidelines carefully - Double-check annotations for consistency - Maintain naming and folder structure - Communicate clearly and respond fast - Deliver clean datasets ready for training You get reliable, scalable annotation support for your ML pipeline. Send your sample task or guidelines. I will start quickly and deliver fast.