Pytorch jobs
...recommendation and ranking pipeline for several enterprise products and I need a senior-level engineer who already lives and breathes these systems. Your primary playground will be large-scale feature engineering and EDA, then building, tuning and shipping models that actually move CTR/CVR metrics in the wild. Here’s the environment you’ll be stepping into: Python and Spark for data prep, TensorFlow/PyTorch for model work, all running on AWS — S3, EMR and SageMaker. GenAI/LLM/RAG methods are in scope; I’m especially interested in seeing how you weave retrieval-augmented generation into ranking logic. You should be comfortable: • Designing and maintaining a feature store, then creating training/validation sets • Building custom neural networks a...
...polish of language plus a critical check of the scientific narrative, calculations, and reported metrics. No generative AI or automated writing tools may be used at any stage. Scope of work • Copy-edit grammar, spelling, and flow while retaining my academic voice. • Strengthen scientific explanations, notation, and figure/table captions where clarity is lacking. • Run the provided code (PyTorch + standard Python libraries), replicate the key experiments, and confirm that numbers in the draft match the reproduced outputs. • Flag any discrepancy in results or methodology and suggest precise fixes; inline comments in the PDF/LaTeX source are fine. • Deliver a clean submission-ready version plus one track-changes or commented file for my own learni...
I need an end-to-end AI automation solution built around unsupervised learning models. My main goal is to ingest raw data, discover hidden structures or groupings automatically, and trigger follow-up actions without manual oversight. Here’s the flow I’m envisioning: you help me prepare and normalise the...training, and inference • Documentation explaining the algorithm choice, hyper-parameters, and how to retrain with fresh data • A simple interface or notebook that visualises clusters, anomalies, or other discovered patterns • Deployment script or Dockerfile so I can spin everything up in one step If you have experience automating pipelines with tools such as scikit-learn, TensorFlow, PyTorch, or similar, and can balance model performance with...
...produce short, coherent passages consistent with the underlying signals in the data. You’ll take the raw vectors, handle any additional preprocessing, select suitable Natural Language Processing architectures—Transformers, LSTM hybrids, or anything you can justify—then train, validate, and fine-tune until performance is solid. Helpful toolkits are totally up to you; I’m comfortable with Python, PyTorch or TensorFlow, Hugging Face Transformers, and scikit-learn if they make the pipeline smoother. Deliverables I expect: • Jupyter notebooks or .py scripts with clear, reproducible code • Trained model weights and tokenizer files • A concise README explaining environment setup and how to run inference • Brief evaluation report showi...
...product and need a developer who can own the build from architecture to store release. The vision is an application that understands day-to-day site queries, learns from project data and offers smart, context-aware suggestions that make life easier for contractors and project managers. You’ll advise on the best way to combine mobile development with machine-learning frameworks such as TensorFlow, PyTorch or a suitable cloud service, then implement, train and integrate the models directly into a clean, intuitive interface. I’m open to your preferred tech stack as long as the final result is maintainable and well-documented. Deliverables • Production-ready mobile app (cross-platform or native) compiled and installable • Trained AI models fully integrated...
...as complementary signals, learns their joint representation, and outputs a binary (disease / no-disease) or probabilistic risk score. Here is what I need from you. First, a clean data-pipeline that ingests my gene expression matrices alongside the associated clinical notes, handles any necessary tokenisation or normalisation, and keeps sample alignment intact. Second, a well-documented model—PyTorch or TensorFlow is fine—that includes separate encoders for each modality and a fusion layer able to capture cross-modal interactions before the final prediction head. Finally, solid training and evaluation scripts with clear metrics such as AUC, accuracy, precision-recall and, ideally, an ablation option so we can see the added value of each modality. Deliverables &bull...
...need a small, self-contained AI solution that can automatically create original, royalty-free, 15-second classical music reels ready for Instagram. The reels are meant purely for entertainment, so each piece should feel fresh, engaging, and unmistakably classical while still sounding modern enough to hold a scroller’s attention. Here’s what I’m after: • A model or pipeline (Python, TensorFlow/PyTorch, or a comparable framework) that composes and renders short classical-style tracks on demand. • Optional lightweight interface—command line or a simple web page—where I choose how many reels I want and instantly receive downloadable audio (or .mp4 with a static cover if that speeds posting). • Output that meets Instagram’s lengt...
I am looking exclusively for a local UAE-based developer...stakeholders can see live KPIs. • If source data is missing, the plug-in quietly launches a web-scraper (Python) to grab supplier specs and fills the gaps before updating Airtable. Acceptance criteria 1. Signed-installer (.msi or .exe) that adds a ribbon tab in Inventor 2024+ with the above workflow. 2. Python source, neatly documented, including the computer-vision model (TensorFlow or PyTorch—your choice) and the web-scraping routines (BeautifulSoup/Scrapy). 3. REST hooks or direct connectors for Airtable and Power BI proven to work with my API keys. 4. Short video demo plus a written deployment guide. If something in the toolchain needs tweaking, I’m open to suggestions—as long as Python...
...descriptions into full 2D animated videos—no manual key-framing required. The goal is an end-to-end pipeline that ingests text, generates the storyboard and assets, and stitches everything together into a smooth, short video (think explainer-style pieces up to a couple of minutes). Here is the scope I have in mind: • Core model: leverage or fine-tune existing diffusion/transformer frameworks (PyTorch or TensorFlow preferred) so the system can produce consistent characters and backgrounds frame-by-frame. • Animation logic: interpolate poses and lip-sync automatically; output 1080p, 24 fps MP4. • Interface: a lightweight web app where I can paste a script, set scene breaks, and press “Generate”. • Deliverables: clean, well-commented so...
...ur reply Do not waste your time. Be PRECISE OK? Scope • Cover the full spectrum of modern AI: classic machine-learning workflows, natural-language processing, computer vision, and emerging multimodal techniques. • Wherever a concrete example fits—image classification, text generation, or small end-to-end projects—walk through the code step by step. Feel free to showcase TensorFlow, PyTorch, Keras, or any other mainstream library if it helps keep explanations clear and practical. • Position every lesson for self-paced study: concise theory, a runnable notebook or script, annotated output, plus brief “Why this matters” commentary to keep motivation high. Deliverables 1. Structured tutorial content (written or slide deck) paire...
...strong experience in CUDA kernels, PyTorch, and performance optimization. Work setup: Remote work through AnyDesk or another remote desktop tool. You will work directly on my development environment. Tasks involve debugging, improving, and optimizing CUDA implementations. Each task typically requires around 3 hours of focused work. Payment: Rate: $8–$10 per hour depending on experience. Payment will be released after 2 weeks of completed work. This is intended to become a long-term working relationship with regular tasks. Required skills: Strong C++ programming skills. CUDA kernel development experience. Understanding of GPU memory optimization, CUDA streams, and kernel performance. Experience debugging CUDA correctness issues. Knowledge of PyTorch CUDA ...
...and optimising Python-based endpoints that expose LLM features to our web and mobile clients. You should feel at home writing clean, test-covered code in FastAPI (or a comparable framework) and managing everything that makes an API reliable—auth layers, rate-limiting, logging, CI/CD, and containerisation. Although the core models are LLMs, familiarity with common AI stacks such as TensorFlow, PyTorch or Scikit-Learn will help when we experiment with alternative architectures. Key deliverables • A version-controlled codebase in Python that wraps our existing LLM checkpoints behind REST (or gRPC) endpoints • Dockerfile and deployment scripts for staging and production • Unit and integration tests with ≥90 % coverage, plus concise Swagger/OpenAPI docs ...
I need a Senior Computer Vision and Deep Learning Engineer to build a complete production-r...edges. This is not a basic rembg installation and no hidden third-party paid API should be used. The developer will be responsible for the complete project, including AI model selection/fine-tuning, Python FastAPI backend, GPU optimization, frontend integration with my existing PHP/JavaScript website, testing, bug fixing, deployment and production launch. Required technologies include Python, PyTorch, OpenCV, image segmentation, alpha matting, ONNX/TensorRT, CUDA, Docker and GPU deployment. Complete source code, trained model weights, training scripts, deployment files and documentation must be handed over. Payment will be milestone-based after quality and speed testing against a privat...
...strong experience in CUDA kernels, PyTorch, and performance optimization. Work setup: Remote work through AnyDesk or another remote desktop tool. You will work directly on my development environment. Tasks involve debugging, improving, and optimizing CUDA implementations. Each task typically requires around 3 hours of focused work. Payment: Rate: $8–$10 per hour depending on experience. Payment will be released after 2 weeks of completed work. This is intended to become a long-term working relationship with regular tasks. Required skills: Strong C++ programming skills. CUDA kernel development experience. Understanding of GPU memory optimization, CUDA streams, and kernel performance. Experience debugging CUDA correctness issues. Knowledge of PyTorch CUDA ...
...行動電話, 險種名稱 and any other handwritten box on the page—that must be recognised automatically. Rather than hard-coding coordinates, I want to call the software with a list of field labels (for example “name” and “address”) and receive the recognised text for each label in a clean machine-readable format such as JSON or CSV. Internally you are free to use OpenCV, PaddleOCR, Tesseract, TensorFlow, PyTorch—or any combination—so long as the handwriting recognition works reliably on Chinese characters and can be extended if new labels are added later. Deliverables: • A runnable script or small service (Python preferred) that accepts a single image/PDF upload and returns the extracted values. • Clear instructions for installati...
...models, validate them against business KPIs, and work side-by-side with product and cloud engineers to deploy your work. Everything is green-field, so you’ll have freedom in approach provided you deliver clean, maintainable code. Must-haves • Deep command of Python for data processing, experimentation, and micro-service development (our core language). • Practical experience with TensorFlow, PyTorch, or a comparable framework, plus a solid grasp of feature engineering, experiment tracking, and MLOps principles. • Comfort with cloud services (AWS, GCP, or Azure) and containerisation so your models ship smoothly. Deliverables 1. End-to-end prototype of at least one core model, complete with well-documented Python code. 2. Concise technical write-up ...
...development—no data wrangling or system plumbing—so I expect clean, well-documented Python modules that import neatly and respect our current project structure. You’ll work against the latest commit in our private Git repo, build out the ML logic we’ve specced (classification and ranking models to start), and deliver passing unit tests so the CI pipeline stays green. Feel free to lean on scikit-learn, PyTorch, or TensorFlow if they keep things elegant and maintainable; the end goal is fast, accurate models that can be called from Dynamo’s core services with minimal overhead. Deliverables • Python source files implementing the requested algorithms • Corresponding unit/pytest coverage ≥ 90 % • Brief README explaining model assumptio...
...students who want to apply Python-driven machine learning to a genuine archaeological problem. The mission is clear: build an AI model capable of reading an undeciphered script, pushing the limits of CNNs and related deep-learning techniques. Your day-to-day focus will be on designing, training, and iterating the model—from data pipelines in Python through to hyper-parameter tuning in TensorFlow or PyTorch—until we reach publishable accuracy. For context, you’ll be working with: • Images of ancient scripts • Transcriptions of ancient texts • Annotated historical data Expect hands-on experimentation with OCR, image augmentation, and transfer learning, plus frequent reviews with archaeologists to validate outputs. I’ll provide mentori...
...(CSV/JSON) as the sole training source, complete with field explanations and sample records. I am open to whichever learning objective—classification, regression, or clustering—best suits the patterns you discover in the data, and I welcome your guidance on choosing the most effective approach. Deliverables I need from you: • A fully trained model in a portable format (TensorFlow SavedModel, PyTorch .pt, or ONNX). • A lightweight inference script or REST endpoint my app can call directly. • Clear documentation covering input schema, preprocessing steps, evaluation metrics, and future fine-tuning instructions. The surrounding pipeline and UI are already in place, so once the model and inference layer are ready, integration should be straightforw...
...reports, dashboards, or predictive models that guide business strategy. Here’s the current picture: • The priority is data analysis and insights, not simply model building for its own sake. • I have access to several structured and unstructured datasets; you can help determine which are most valuable and how best to preprocess them. • Flexibility around tools is important—Python, R, TensorFlow, PyTorch, scikit-learn, or cloud services such as AWS SageMaker and Google Cloud AI are all possibilities as long as the final solution is reproducible and well-documented. Key deliverables I’m looking for: 1. A clear, well-commented codebase or notebook that ingests the agreed data, cleans it, and applies the chosen algorithms. 2. An explanation (wr...
...detection • trend prediction • behavioral analysis • pattern recognition • forecasting ________________________________________ Dashboard Modern executive dashboard including: • KPIs • alerts • analytics • reporting • visualization • customizable widgets ________________________________________ Preferred Technology Backend • Python • FastAPI • PostgreSQL • Neo4j • Elasticsearch • Redis • Kafka AI • PyTorch • TensorFlow • LangChain • Llama • Vector Databases • RAG Frontend • React • TypeScript • Mapbox • D3.js or Infrastructure • Docker • Kubernetes • AWS or Azure • CI/CD ________________________________________ Deliverables &b...
...routine content updates or data-driven sections so the site stays fresh with minimal manual input. Platform choice is open. WordPress, Shopify, or a fully custom stack are all possible as long as the final build remains scalable, secure, and easy for a non-technical team to manage. Recommend whichever stack will integrate smoothly with services such as OpenAI, Dialogflow, or custom TensorFlow/PyTorch models. Deliverables 1. Wireframes and final responsive UI/UX. 2. Fully developed site with the three AI features above working end-to-end. 3. Admin dashboard and clear documentation for future maintenance. 4. Deployment to our hosting of choice plus a short hand-off session. Acceptance criteria • Pages load in under 2 s on mobile and desktop. • Chatbot repli...
... end-to-end computer-vision system that can spot diseases across three domains—human healthcare, crop agriculture, and veterinary practice—without ever calling external APIs. Scope • Training: You’ll design and train deep-learning models to recognise Cancer in medical scans, Plant Fungal Infections in leaf images, and Animal Parasitic Infections in animal skin images. Feel free to choose PyTorch, TensorFlow or another modern framework, but the workflow must run entirely on local hardware after setup. • Data: Combine public datasets and clear instructions for adding private data so future users can extend or fine-tune. • Inference: Produce a lightweight CLI (a small GUI is a bonus) that accepts single images or folders, returns class label...
...back-ends. Core responsibilities • Design and implement reproducible ML pipelines in Python. • Optimise training workflows for speed, cost, and accuracy. • Evaluate, version, and monitor models once they’re in production. • Collaborate with the cloud and full-stack teams to expose prediction services via robust APIs. Acceptance criteria • A functioning training pipeline (ideally using PyTorch or TensorFlow) that runs end-to-end on our AWS account. • Clear documentation and unit tests. • Demonstrable improvement over baseline benchmarks we will provide. If you also enjoy Rust, Rails, or architecting large-scale cloud infrastructures, there will be plenty of space to apply that expertise as the product grows. When you submit a ...
...through a lightweight FastAPI endpoint that I can drop into my existing stack. Here is what I need done: • Curate or expand an annotated dataset that covers cars, trucks, bikes, pedestrians, and common domestic or wild animals in varied lighting and weather conditions. • Train and fine-tune an object-detection model—YOLOv8, Faster-RCNN, or another state-of-the-art architecture in TensorFlow or PyTorch is fine as long as it balances accuracy and inference speed. • Validate the model with mAP, precision/recall, FPS, and confusion-matrix reports, then iterate until it meets the agreed thresholds. • Package the final weights and inference code behind a FastAPI REST endpoint that accepts an image file or base64 string and returns JSON bounding boxes,...
Job Description: I'm running a self-hosted, real-time conversational voice AI pipeline (STT → LLM → streaming TTS over WebSocket) on a RunPod GPU pod (CSM-1B TTS model, using the davidbrowne17/csm-streaming fork with Sesame's Mimi/moshi audio codec, PyTorch ). I need an experienced PyTorch/CUDA engineer to find and fix a reproducible latency bug that's blocking production readiness. The problem: At sentence/turn boundaries in a multi-turn conversation, generation stalls for ~7-8 seconds of dead air. I've already localized this precisely via wall-clock instrumentation: the stall occurs specifically inside Mimi's () call, when encoding a previous turn's generated audio into context — and specifically only w...
...Explore and implement Machine Learning techniques where applicable. Collaborate with domain experts to develop innovative software solutions. Participate in software testing, validation, documentation, and continuous improvement. Required Skills Strong proficiency in Python. Experience with NumPy, Pandas, and SciPy. Knowledge of Machine Learning using frameworks such as scikit-learn, TensorFlow, or PyTorch. Experience with SQL or other database technologies. Familiarity with Git and software development best practices. Strong analytical, mathematical, and problem-solving skills. Ability to understand technical concepts and translate them into software solutions. Preferred Skills Experience with optimization algorithms or scientific computing. Knowledge of data visualization tools...
...in mind 1. User snaps or imports a food image. 2. The app detects and segments each food item in the photo. 3. It matches each segment to a nutrition database and scales the values by estimated portion size. 4. Results are shown clearly on-screen and saved locally for later review. Technical direction • Target platform: Android only. • Feel free to leverage TensorFlow Lite, ML Kit, PyTorch Mobile or any other on-device vision stack you are comfortable with, as long as the APK remains lightweight and runs without cloud connectivity. • A small cloud fallback for edge cases is acceptable, but the core analysis should work offline. • Source code, model files, and a brief README explaining model training or fine-tuning steps form the final delivera...
...(LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, or similar). >Experience building Generative AI and Retrieval-Augmented Generation (RAG) applications. >Fine-tuning and optimization of Large Language Models (LLMs). >Experience with vector databases such as Pinecone, Milvus, Weaviate, FAISS, or ChromaDB. >Knowledge of LangChain, LlamaIndex, and AI orchestration frameworks. >Strong understanding of PyTorch, Hugging Face Transformers, and model optimization techniques. >Experience deploying AI workloads on AWS (EKS, SageMaker, EC2, Bedrock, or equivalent cloud services). >Experience designing RESTful APIs, gRPC services, Docker, Kubernetes, and CI/CD pipelines. >Familiarity with cybersecurity concepts such as SIEM, SOC operations, threat intelligence, vulnerab...
...etc. 3. Output a GPS fix (lat/long) for every confirmed object. 4. Provide a lightweight runtime that can run either on the drone’s onboard computer or a nearby edge server with minimal latency. 5. Deliver documented test results on real or simulated runway scenes demonstrating the required accuracy in day and night scenarios. Deliverables • Source code and trained weights (TensorFlow, PyTorch or similar). • Deployment script or container. • Brief technical report summarising methodology, training data used, evaluation metrics and performance. Acceptance criteria When I feed the system a representative data set captured from the drone, it must detect ≥95 % of the target items with <5 % false alarms and return GPS coordinates within a m...
...Optimize Whisper or evaluate alternative multilingual ASR approaches * Build confidence scoring and error handling for low-confidence transcripts * Improve acoustic and linguistic feature extraction * Benchmark model performance using objective evaluation metrics * Document findings and recommendations * Work closely with the founding team on iterative experiments --- ## Required Skills * Python * PyTorch * Speech AI / ASR * Whisper or similar speech models * Hugging Face * Audio processing (Librosa, Torchaudio, etc.) * FastAPI * Git --- ## Preferred * Experience with multilingual ASR * Hindi/Hinglish speech processing * Code-switching research * Healthcare AI or cognitive assessment * Model evaluation and benchmarking --- ## Deliverables By the end of the engagement, th...
...development—no data wrangling or system plumbing—so I expect clean, well-documented Python modules that import neatly and respect our current project structure. You’ll work against the latest commit in our private Git repo, build out the ML logic we’ve specced (classification and ranking models to start), and deliver passing unit tests so the CI pipeline stays green. Feel free to lean on scikit-learn, PyTorch, or TensorFlow if they keep things elegant and maintainable; the end goal is fast, accurate models that can be called from Dynamo’s core services with minimal overhead. Deliverables • Python source files implementing the requested algorithms • Corresponding unit/pytest coverage ≥ 90 % • Brief README explaining model ass...
I’m building a responsive web app that runs smoothly on any iPhone browser and on Windows desktops. Its co...sub-5-second odds refresh and sub-60-second player/weather updates 3. Documented data sources, model methodology, and environment setup instructions 4. Admin panel for adding new bookmakers or tweaking model parameters 5. Automated tests covering data ingestion, model outputs, and UI critical paths I’m flexible on the final tech stack—React or Vue on the front end, Python (TensorFlow, PyTorch, or XGBoost) or a Node alternative for the AI layer are all fine as long as they deliver speed and transparency. Let me know how you’d structure the data feeds, what modelling approach you would use, and any previous work that proves you can bring real-ti...
...--- ## MLOps & Production Engineering Experience with: * Docker * Kubernetes * CI/CD pipelines * MLflow * Model versioning * Model deployment * Model monitoring * Experiment tracking * Feature stores * GPU inference optimization * REST APIs (FastAPI preferred) Cloud experience with at least one platform: * AWS * Google Cloud Platform * Microsoft Azure --- ## Nice to Have * Deep Learning (PyTorch or TensorFlow) * Fine-tuning LLMs (LoRA/QLoRA/PEFT) * Distributed training * Knowledge Graphs / GraphRAG * Computer Vision or NLP experience * Reinforcement Learning * Streaming data pipelines (Kafka, Pub/Sub) * Airflow or similar orchestration tools * Experience building AI agents for enterprise applications --- ## What We're Looking For The ideal candidate is: * Str...
...code needs to read the rule in , choose the right metric direction automatically and optimise accordingly. I picture the workflow like this: 1. The user drops the four task files into a fresh directory. 2. They run python solution.py. 3. The script detects the data type, the metric orientation and the task family, trains the best available model (scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow, Hugging Face transformers—use whatever fits), and writes ready for upload. Acceptance criteria • runs with `python3 ` on a clean machine (specify any pip installs). • The script finishes inside a sensible time window on a single GPU or CPU-only fallback. • It produces a numeric score close to the current public leaderboard baseline for
...Once the data layer is solid, the core requirement is a fault-detection model that can recognise patterns linked to hardware problems—temperature spikes, power irregularities, component degradation, and similar signatures. Accuracy, low latency, and clear interpretability matter more to me than cutting-edge algorithms for their own sake, so please choose whatever combination of Python, TensorFlow/PyTorch, or any proven libraries you prefer as long as it makes the results easy to explain and monitor. I also want the results surfaced through a lightweight, responsive website. Think dashboard rather than marketing page: live fault alerts, a historical view, and a simple way to download or stream the underlying data. Hosting can be on AWS or another mainstream cloud platform...
...and integrate AI capabilities into user-facing products - Improve system architecture, scalability, reliability, and performance - Collaborate on technical decisions and future AI product development Required Technical Skills - Strong experience with Python and AI/ML development - Experience with AI model training, fine-tuning, and evaluation - Knowledge of machine learning frameworks such as PyTorch, TensorFlow, or similar - Experience building AI pipelines, data processing workflows, and model integrations - Full-stack web development experience - Backend: Python frameworks (FastAPI, Django, Flask, etc.) - Frontend: React, , or modern JavaScript frameworks - Experience designing and integrating REST APIs - Understanding of databases, cloud infrastructure, and deployment workfl...
I’m refining an AI module that powers a heads-up, visually oriented interface. The core engine is Natural Language Processing, yet right now its intent detection and response generation drift off-target too often. I need your help to push raw and benchmarked accuracy noticeably higher without sacrificing latency. You’ll dive into the existing Python codebase (TensorFlow and a light PyTorch utility are already in play), audit the current model pipeline, then propose and implement improvements—be that better tokenisation, a more suitable transformer architecture, advanced data augmentation, or smarter post-processing. The interface overlays results on a visual HUD, so clean, deterministic outputs matter; hallucinations or fluffed confidence scores show up instantly ...
...Example: { "plateNumber": "123456", "country": "Qatar", "plateType": "Private", "confidence": 0.94, "timestamp": "2026-07-07T10:30:00", "cameraId": "CAM-01", "plateImage": "path/to/", "vehicleImage": "path/to/" } Important Requirements: * Developer must have previous experience in ANPR, OCR, object detection, OpenCV, YOLO, PaddleOCR, EasyOCR, TensorFlow, PyTorch, or similar technologies. * The system should be trainable/improvable using our own Qatar/GCC plate dataset. * Accuracy should be tested in day, night, low-light, angled, and moving vehicle conditions. * The final solution should not depend on expensive th...
...way from booking to delivery. Data flow • Primary data source: customer input collected through web forms. • Optional hooks for historical move data or live market rates should be left open but not hard-wired, so the architecture must remain modular. Tech expectations A lightweight front end (React or similar) can sit on top of a Python/Node microservice that hosts the model—TensorFlow, PyTorch, scikit-learn or whichever framework you feel is best for fast iteration. Clean REST or GraphQL endpoints are essential, and everything should be containerised for easy deployment. Deliverables • Customer-facing responsive form that feeds data to the model • Trained price-estimation model with documented feature set • Inventory-management dashb...
...walk-throughs of code where appropriate. Scope • Introduction to AI concepts – history, terminology, ethics, basic math refresh. • Advanced machine learning techniques – supervised/unsupervised methods, deep learning, model evaluation, hyper-parameter tuning. • Practical AI applications – small end-to-end projects that show theory in production, ideally with Python, Jupyter, TensorFlow/PyTorch and relevant datasets. What I will supply – High-level syllabus with learning objectives. – Branding guidelines and lower-third templates. – Access to any datasets or notebooks you may require. What you will deliver 1. Professionally shot HD recordings (1080p or higher) in .mp4. 2. Clean audio, good lighting and steady fr...
...examples of how you’ve shipped AI-driven products so I can model best practices. Scope highlights – Full-stack focus: front end, back end, and the glue that connects them. – Hands-on AI integration: prompt engineering with Claude, code generation and refactoring in Cursor, and React-based interfaces that surface the AI’s output cleanly. – Openness to additional frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) if they help illustrate a concept, but they’re not mandatory. Acceptance criteria 1. A clear syllabus delivered at the outset, broken into logical modules. 2. At least one functioning demo app completed by the end of our engagement, showing an AI feature in production. 3. Written recap after each session capturing decisio...
...My objective is to understand today’s leading architectures—think GPT-style transformers—and then reproduce, extend, and evaluate recent research in natural language processing. Here’s what I need from you: • A clear learning roadmap that walks me through the essential papers, repos, and concepts behind modern text-generation systems. • Hands-on guidance while I set up a Python environment (PyTorch or TensorFlow, Hugging Face Transformers, perhaps LangChain) and fine-tune or train a model on a small dataset. • Practical notebooks that generate text, document the hyper-parameters used, and demonstrate evaluation techniques such as perplexity, BLEU, and human-readability checks. • Regular feedback sessions—screen-sharing, cod...
We are building our project AI-native Music SaaS Platform. The platform allows users to generate high-quality son...Professional, tech-driven, and high-performance environment. Mention your experience with Python FastAPI and AI model integration. Please provide links to your GitHub or a project where you built a complex AI pipeline. Skills required Developer Skills • Python (5–10+ years preferred) • FastAPI • PostgreSQL • Redis • Docker • REST APIs • JWT/RBAC • Async programming • System Design • AI integrations • PyTorch • Hugging Face • ACE-Step • JWhisper • FFmpeg • CUDA • GPU Optimization • ComfyUI We would like to humbly request that the same person who has previously worked on ...
...need an AI solution that takes product photos and sorts each image into fewer than five preset categories. The sole goal here is image classification—no detection or enhancement features are required. You will start from an existing dataset of labelled product images (I’ll supply a download link once we begin). A lightweight, production-ready model built in Python with either TensorFlow or PyTorch is preferred; transfer-learning from a well-known backbone (e.g., ResNet, EfficientNet, MobileNet) is perfectly acceptable so long as the final classifier is accurate and quick to infer on standard CPU hardware. Key deliverables: • Clean, commented source code for training and inference • The trained model weights (or exported SavedModel / .pt file) • ...
...Satellite imagery and GIS layers with AI so I can validate a larger platform idea. The goal at this stage is pure data analysis: ingest the two data sources, run machine-learning workflows that surface patterns or anomalies, then surface the results through a minimal interface or notebook I can demo to stakeholders. A typical stack for me would be Python with GeoPandas, rasterio, TensorFlow or PyTorch, plus PostGIS or a lightweight spatial database—but I’m open if you have a smarter path. What matters is that the pipeline reliably pulls in the imagery and vector layers, cleans and aligns them, applies the models, and outputs clear, reproducible insights. Please attach past work that proves you’ve built something similar—ideally an AI application that tou...
... music and footage) tuned for entertainment niches • Automatic video assembly and aspect-ratio formatting for Shorts • One-click or scheduled publishing with title, description, and hashtag handling • A lightweight dashboard so I can review, approve, or edit clips before they go live I have no fixed opinion on the exact tech stack as long as it scales and stays maintainable; TensorFlow/PyTorch, ffmpeg, Node/React, Python-based backends, or comparable tools are all acceptable if you justify the choice. Clean, well-commented code and deployment documentation are must-haves so I can keep the project running without hand-holding. To help me gauge fit, please link to past work that shows you have built AI or automation pipelines for video, social publishing plat...
...into our current back-end and scales with user demand. • Three automation tracks—predictive analytics, chatbots/virtual assistants, and automated data processing—each exposed through clean API endpoints. • Solid integration glue so these AI services talk to the rest of the SaaS features (auth, billing, dashboards, etc.). I’m flexible on the underlying framework; if you prefer TensorFlow, PyTorch, Hugging Face Transformers, or another proven stack, that’s fine as long as the final service is efficient, secure, and easy to maintain. Acceptance criteria 1. Endpoints return accurate, low-latency responses under load tests we’ll define together. 2. All code is version-controlled with clear readme and environment setup scripts. 3. A sho...
I’m looking for a fully working AI chatbot written in modern C++. The system must ingest structured data that I’ll provide (typically CSV or a small SQL dump) and turn it into co...structured data and stores it for fast look-ups. • Core dialogue logic: intent detection, record retrieval, and natural-language reply generation. • A simple CLI demo (or minimal GUI) that lets me type a question and receive an answer on the spot. • README with build steps, library dependencies, and a short “getting started” guide including an example dataset. Libraries such as TensorFlow C++, PyTorch C++ API, or even a rules-based engine are fine—use whatever achieves accurate replies with low latency. Deliverables are the complete compilable source, e...
