Hire the Best PyTorch Professionals

I build production-ready AI systems (RAG pipelines, LLM applications, and multilingual NLP) that solve real problems, not just demos that break in production. I'm a PhD researcher in AI/ML with 6+ years building NLP, machine translation, and information retrieval systems, with published work in ACM, Elsevier, EACL, and FIRE. That research background means I can handle the hard problems most freelancers can't: cross-lingual retrieval, low-resource and Indic languages, speech-to-speech systems, and LLM pipelines that actually hold up. What I can build for you: ✔ RAG pipelines and LLM-powered applications (LangChain, HuggingFace, PyTorch) ✔ NLP systems: text classification, NER, sentiment analysis, transformers ✔ Multilingual & cross-lingual AI, with deep expertise in Indic languages ✔ Speech-to-text and speech-to-speech AI ✔ Search and information retrieval engines ✔ Custom ML models: supervised, unsupervised, and deep learning ✔ End-to-end AI pipelines, from prototype to deployment I communicate clearly, hit deadlines, and care about code you can actually maintain. If you have an AI/NLP problem you're not sure is even solvable, that's exactly the kind of project I like. Send me a message and let's scope it.

✅ $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 a Machine Learning & Backend Engineer with a strong background in AI, data analytics, and software development. I have hands-on experience building intelligent systems ranging from deep learning models with MobileNetV2 for image classification to reinforcement learning for medical diagnosis support systems. 🔹 What I can help you with: • Machine Learning & Deep Learning: Model training, evaluation, and deployment (XGBoost, Random Forest, TensorFlow, MobileNetV2, BERT). • Computer Vision & NLP: Image classification, data augmentation, OCR, and text analytics. • Backend Development: API design with FastAPI, scalable data pipelines, and cloud integration. • Data Analytics: Data preprocessing, visualization, and predictive modeling. • Healthcare & AI Research: Clinical decision support systems (AI-CDSS), medical data pipelines, and published research (IEEE Scopus Indexed). 💼 Highlights: • Built BerryCare, an AI-powered strawberry disease detection app (MobileNetV2 + FastAPI, Hybrid Edge AI & Cloud). • Currently working at GreyDx (Singapore), developing AI models and backend systems for a Clinical Decision Support System. • Authored and presented a research paper on deep learning at IEEE IAICT 2025. • Holder of 25+ professional certifications (Stanford, DeepLearning.AI, Google, Huawei, etc.). I combine strong technical skills with creativity and collaboration, ensuring every solution is both innovative and practical. If you’re looking for someone who can deliver end-to-end AI/ML solutions or backend systems, I’m here to help. 🚀 Let’s bring your ideas to life with data-driven solutions!

Top Rated Plus ML engineer: medical imaging (segmentation, registration, nnU-Net), clinical NLP, deep computer vision. 100% Job Success · 1,200+ hrs. I take on the problems where the obvious approach fails. WHERE I DO MY BEST WORK Medical imaging ML. I evaluate and debug segmentation models (Dice scores, Bland-Altman analysis), run rigid and deformable image registration (ANTs/SyN), handle nnU-Net preprocessing and training, and deliver 3D Slicer overlays your clinical team can actually inspect. On my longest imaging engagement I sent a demo video at every milestone, so the client never had to guess where things stood. Before Upwork, I worked on chest X-ray segmentation and calcification detection for a US medical-device software company. Clinical & scientific NLP. 600+ hours (and counting) on a research-heavy clinical NLP project: sentence embeddings, UMAP + HDBSCAN clustering, custom composite scoring, synthetic training data. The kind of work where you form a hypothesis, run the experiment, and let the data kill it. (Under NDA) Deep computer vision. I trained a Flux DensePose ControlNet from scratch — dataset prep, captioning, GPU training, parameter tuning — then shipped it behind a Streamlit app so the client's non-technical team could generate images without me. Also: YOLO detection, and an automated color-correction pipeline that detects a color card and generates 3D LUT/CUBE files across EXR, CR2, CR3, and PNG workflows. Document intelligence & LLM pipelines. I build document-processing pipelines that extract structured data from messy PDFs, scans, invoices, and reports — OCR, transformer-based page classification, and LLM extraction with Claude/OpenAI — delivering clean CSV or JSON. I've also built cross-referencing systems that connect information across multiple documents, and raised extraction accuracy on a pipeline other teams had given up tuning. I ALSO GET CALLED WHEN SOMETHING IS SILENTLY BROKEN Two of my favorite projects were rescues: a Temporal Fusion Transformer backtest that was silently leaking data (fixed the encoder/decoder windowing, ran leakage checks, rebuilt walk-forward validation), and a multi-timeframe trading pipeline writing empty tags (root-caused it, patched it, added audit scripts and trace columns). If you need someone to debug and fix an ML model, training pipeline, or backtest that's producing numbers nobody quite trusts, that is a job I know how to do. HOW I WORK Fast replies — usually within hours, working Nepal time with real overlap across US, EU, and AU hours. Milestone demos, often as short videos. Documentation your next engineer can pick up cold. All 13 of my completed contracts are five stars, and several reviews use the phrase "above and beyond", that part I'm proud of. Send me the problem you suspect is too messy for a freelancer. Those are the ones I want.

AI & Machine Learning Engineer | NLP | Generative AI | LLMs | Prompt Engineering | Data Science I help businesses build intelligent systems that work — at scale, in production, and with measurable results. With 3+ years of hands-on experience as an ML and AI Engineer, I specialize in: ✅ Machine Learning & Predictive Modeling — Building and deploying ML models using Python, TensorFlow, Scikit-learn, and PyTorch for regression, classification, forecasting, and recommendation systems. ✅ Generative AI & LLMs — Developing RAG pipelines, AI chatbots, and custom LLM applications using OpenAI GPT, LangChain, and Hugging Face Transformers. Fine-tuning models for domain-specific tasks. ✅ NLP & Text Analytics — Sentiment analysis, topic modeling, text classification, named entity recognition (NER), and document processing pipelines. ✅ AI Engineering & MLOps — End-to-end AI system design, REST API development with FastAPI/Flask, model deployment on AWS/Azure/GCP, and CI/CD for ML pipelines. ✅ Prompt Engineering — Crafting optimized prompts for GPT-4, Claude, and other LLMs to maximize accuracy, relevance, and brand alignment for business applications. ✅ Computer Vision — Object detection (YOLO), image segmentation, OCR, and real-time video analytics systems. ✅ Data Analytics & Visualization — Power BI dashboards, SQL-based data pipelines, and actionable business intelligence reports. Tech Stack: Python | TensorFlow | PyTorch | Scikit-learn | LangChain | OpenAI API | Hugging Face | FastAPI | Flask | AWS | Azure | SQL | Power BI | Docker I hold a PhD in Data Science (University of Canterbury) and an MPhil in Computer Science (Quaid-e-Azam University), plus certifications from DeepLearning.AI and AWS. Whether you need an ML model built from scratch, an AI chatbot integrated into your product, or a full generative AI pipeline — I deliver production-ready solutions, not just experiments. Let's build something intelligent together.

Do you have an AI vision that needs to become a real, working product? I don't just build models; I engineer complete, scalable solutions that turn data into actionable insights and automation. For over five years, I've specialized in bridging the gap between cutting-edge Artificial Intelligence (AI) research and robust software that delivers real-world value. My core expertise lies in computer vision and machine learning, but my skill set is full-stack. This means I can own your project from the initial data pipeline, through model training and optimization, all the way to deploying a polished desktop application or a secure enterprise API. I thrive on building tools that work seamlessly for end-users, whether it's a retail manager, a traffic controller, or a sports coach. My strongest suit is developing intelligent systems that "see" and understand the world. I've built a retail analytics platform (CrowdIQ) that transforms standard CCTV into a source of business intelligence, tracking customer demographics and behavior. In the sports domain, I created PadelIQ, an analytics engine that uses computer vision to track player movement, posture, and court coverage from match footage, providing real-time coaching feedback. For public safety, I developed a traffic management system (OmniRoad AI) using advanced object detection for real-time accident and congestion monitoring. Beyond computer vision, I architect full-scale data science pipelines. A prime example is my telecom churn prediction project, where I built a machine learning model to identify at-risk customers and paired it with an interactive Power BI dashboard. This end-to-end approach—from data analysis to a clear visualization of insights—ensures the model's findings directly inform business strategy and retention actions. I also develop the tools and infrastructure that power AI applications. I've built secure, enterprise-grade systems like DevelmoGPT, a RAG-based LLM that allows for secure, semantic search over private company documents. From creating simple utilities like PDF-to-audio converters to designing complex role-based access systems, I ensure the foundation of any AI solution is reliable, secure, and maintainable. My process is collaborative and results-driven. I start by deeply understanding your business problem, not just the technical requirement. We'll then iterate through prototyping, development, and testing to ensure the final product not only meets specs but also delivers tangible ROI. I communicate clearly at every stage, providing demos and documentation so you're never in the dark. Let's connect. Share your project idea or challenge, and I'll provide a clear outline of how we can leverage AI, machine learning, or computer vision to build your intelligent solution. Click the invite button to start the conversation. /// The following is just for SEO. You can ignore it /// #computer vision #computer vision engineer #computer vision OpenCV #machine learning computer vision #deep learning computer vision #computer vision machine learning #machine learning python #nlp machine learning