Pytorch jobs

I want to guide a small group of absolute beginners all the way to the point where they can land an entry-level role in AI, machine lea...job-ready competence; guidance on refining those projects for GitHub and technical interviews. • Ongoing Q&A support—Slack, Discord or similar—and lightweight progress checkpoints so nobody falls behind. • Suggestions for open-source contributions, Kaggle competitions or hackathons that fit naturally into the timeline. I’m flexible on tools as long as they are industry-relevant—TensorFlow, PyTorch, Hugging Face, LangChain, Google Colab or local GPU setups are all fine. Please outline how many weeks you’d need, the approximate hours of live contact, and what deliverables (slides, notebooks, code repo...

I have several ongoing initiatives that each require their own AI agent—some conversational, others focused on data extraction or decision support. I need someone who can take an idea, choose an appropriate framework (for example, Python with LangChain or Rasa for chat, TensorFlow or PyTorch for analysis-heavy tasks), and turn that into a production-ready microservice or packaged module. Typical flow • Review the project brief with me and translate objectives into agent capabilities • Propose the tech stack and model choice, clearly explaining trade-offs • Build, test, and fine-tune the agent, then expose it through a clean API or SDK • Hand over clear documentation and lightweight maintenance scripts (Docker or similar) Because each project differs...

...machine-learning models so I can focus on creative direction instead of button-pushing. Because the exact feature mix is still open, I’m especially interested in solutions that can easily expand to cover automatic scene detection, audio clean-up and smart title/text overlays as the project grows. Feel free to propose a framework you know well—whether that’s Python with OpenCV, a TensorFlow or PyTorch model, or an integration on top of Adobe’s SDK—so long as the final result runs on Windows and outputs standard formats (MP4, MOV). Deliverables I expect at this stage: • A working prototype capable of ingesting at least one sample video, applying AI-powered edits, and exporting a finished file • Source code with clear comments and setup ...

...methodology, training process and inference workflow * Recommendations for scaling the model to larger areas of Jharkhand Ideal Candidate Please apply if you have demonstrated experience in: * Remote sensing and satellite image processing * Computer vision / deep learning * Tree detection and crown segmentation * Tree species classification * GIS / GeoPandas / Rasterio / Google Earth Engine * Python, PyTorch/TensorFlow * Models such as DeepForest, YOLO, Mask R-CNN, U-Net, SAM or similar * Multispectral/hyperspectral imagery * Geospatial AI Experience with forest/tree species mapping is highly preferred....

...enough to extend into stocks later, that’s a plus but not required right now. • Actionable outputs are essential. Whether through a lightweight dashboard, e-mail/SMS alerts, or direct API calls back into my broker, I need clear “risk heat” indicators and recommended de-risking steps (reduce size, tighten stops, hedge, etc.). I’m comfortable with Python, so a solution built around TensorFlow, PyTorch, or similar libraries will slot easily into my workflow, but I’m open to other stacks if you can justify the benefit. Just make sure any data feeds you rely on (price, order-book depth, news sentiment) are either free or come with clear cost estimates. Deliverables: • A working AI model that ingests live forex and crypto data and outputs...

... the raw scenes are already orthorectified and radiometrically corrected. What I’m missing is the machine-learning layer that will take two (or more) aligned images, learn the patterns of normal variability, and then output clear, georeferenced change masks and summary statistics. Key expectations • Model architecture, training pipeline, and inference script packaged in Python (TensorFlow, PyTorch, or another proven deep-learning framework). • Clear instructions for reproducing results on my own machine, including environment file and command-line steps. • Evaluation report showing accuracy metrics on a held-out test set I will provide after initial proof of concept. If you have experience with satellite imagery, convolutional networks, and change d...

...tables, and every element must stay exactly where it is on the page—headings, figure numbers, table captions, footnotes, everything. Only the language changes; the layout does not. Because the piece is earmarked for formal publication, I expect precise terminology, consistent tone, and zero tolerance for ambiguity or machine-style phrasing. References to frameworks, model names, or metrics (e.g., PyTorch, Transformer-based encoder accuracy, ROC-AUC) must be rendered in the same professional style used by leading AI journals. If a sentence can carry more than one meaning, add a short translator’s note so we can verify intent together before final sign-off. Deliverables • A fully translated Word file that mirrors the Japanese original in structure, tables, figu...

...staff. • Adjust roles or permissions instantly without digging through code. Core deliverables 1. Web or hybrid mobile app for customers, staff, and couriers with a clean ordering workflow. 2. Admin dashboard built with a modern framework (React, Vue, or Angular is fine) plus backend APIs. 3. Integrated AI modules (recommendation system, chatbot) using your preferred stack—TensorFlow, PyTorch, Dialogflow, or similar—as long as setup instructions are provided. 4. Source code in a private Git repo, environment setup guide, and short video walk-through so I can test everything myself. I’m ready to move quickly once I see a concise plan and timeline. Let me know which stack you’d propose and any previous projects that show you can handle u...

...see how it performs on both real and fabricated pieces. The workflow I have in mind combines three parts: • an automated pipeline that scrapes or ingests fresh articles, cleans the text, and stores it in a structured format; • a robust NLP model—think transformer-based architecture fine-tuned on a well-curated fake-vs-real news dataset—trained and evaluated in Python with libraries such as PyTorch, TensorFlow or Scikit-learn; • a lightweight interface (REST API or simple web demo) that returns the probability of falseness plus the key features that influenced the decision for transparency. Deliverables • End-to-end codebase with clear instructions ( / , README) • Trained model weights and scripts to reproduce training and evaluatio...

...identify physically implausible or anomalous motion. Generate explainable alerts, e.g., why an event was classified as high risk. Provide confidence/risk scores for detected events. Include basic privacy-preserving mechanisms, such as face/person anonymization where required. Provide a visualization/dashboard showing detected objects, trajectories, and alerts. Expected Technical Skills : Python, PyTorch, Deep learning, Physical AI Preferred Candidate Candidates with a background in Computer Vision, Physics-Informed Machine Learning, Video Analytics, AI/ML research, or Intelligent Surveillance Systems will be preferred. Please include relevant previous projects/GitHub/demo links and briefly explain your experience with physics-aware AI or video analytics. For background on our ...

...transformation pipelines. * Develop, deploy, and monitor machine learning models. * Clean and organise messy data from different sources. * Translate business needs into practical data or ML solutions. * Document systems, processes, and technical decisions. * Work independently and collaborate in English and Spanish. Requirements * Strong Python, pandas, NumPy, and scikit-learn skills. * Experience with PyTorch or TensorFlow. * Advanced SQL knowledge. * Experience with Airflow, Prefect, Dagster, or similar tools. * Knowledge of at least one cloud platform. * Fluent spoken and written English and Spanish. Experience with Spark, dbt, Docker, MLOps, LLMs, or an early-stage startup is helpful but not required. To apply, send your CV and a short description of something you built,...

...see how it performs on both real and fabricated pieces. The workflow I have in mind combines three parts: • an automated pipeline that scrapes or ingests fresh articles, cleans the text, and stores it in a structured format; • a robust NLP model—think transformer-based architecture fine-tuned on a well-curated fake-vs-real news dataset—trained and evaluated in Python with libraries such as PyTorch, TensorFlow or Scikit-learn; • a lightweight interface (REST API or simple web demo) that returns the probability of falseness plus the key features that influenced the decision for transparency. Deliverables • End-to-end codebase with clear instructions ( / , README) • Trained model weights and scripts to reproduce training and evaluatio...

...craft a new architecture in PyTorch, schedule distributed training, and iterate until the model achieves reliable closed-loop visuomotor reasoning in simulation and on hardware. Robust multimodal representation learning, a world-model/JEPA component, temporal memory, and predictive control need to come together in a single, maintainable codebase. I handle the robot side, so you can stay laser-focused on the Vision-Language-Action models themselves, while still having access to logs and live telemetry from our arms and mobile bases. If your approach can integrate ideas from the broader Robotic Intelligence literature or streamline the research-to-deployment pathway, that flexibility is welcome, but not mandatory. Deliverables • Clean, well-documented PyTorch implem...

...later, phase one focuses exclusively on perfecting these recommendations. Technical expectations • End-to-end platform or plug-in capable of integrating with common stacks (Shopify, WooCommerce, custom React/Node, etc.). • Scalable data pipeline—batch and real-time—to capture events, train models, and serve predictions with low latency. • Model layer leveraging proven libraries (TensorFlow, PyTorch, or similar) and techniques such as collaborative filtering and deep learning for cold-start mitigation. • Admin dashboard for A/B testing, rule overrides, and performance analytics (CTR, AOV lift, revenue attribution). Deliverables 1. Deployed, production-ready storefront or extension with live product-suggestion widgets. 2. Source code repository...

...cross-disciplinary “general AI” scope rather than being limited to NLP, Computer Vision, or Reinforcement Learning alone. I need a collaborator who can help shape the research question, set up experiments, analyse results, and co-author the manuscript to publication standard. Key phases • Literature mapping to identify a novel research gap • Experimental design and implementation (using Python, PyTorch / TensorFlow, or similarly capable stacks) • Rigorous evaluation with reproducible code and well-documented datasets • Full paper write-up—including abstract, methodology, results, discussion, and formatted references—ready for submission Acceptance criteria • Manuscript of roughly 8–10 pages (IEEE two-column or com...

...on topic, and preserves an appropriate tone of voice. You’ll work with my existing dialogue data (plus any open-source corpora you recommend) to create a model that can: • Understand multi-turn context and user intent • Respond naturally in English without hallucinating facts • Respect soft constraints I’ll provide on length, formality, and persona Typical tools in this space—Python, PyTorch or TensorFlow, Hugging Face Transformers, and popular evaluation libraries—fit well here, but I’m flexible if you have a stronger stack. Deliverables 1. Pre-processed, reproducible dataset and accompanying scripts 2. Fine-tuned model checkpoints with clear versioning 3. Inference wrapper (REST API or lightweight microservice) that I...

...the next step. The system must automatically cut and splice raw footage, apply colour-accurate corrections, and drop in context-aware special effects, then go a step further by generating entirely new video clips and still images from text or style prompts. Here’s what I want the tool to handle for me: • AI video editing • AI video generation • AI image generation Preferred tech includes PyTorch or TensorFlow for the modelling work, diffusion or transformer architectures for generation, and FFmpeg for final rendering, yet I’m open to any stack you can justify that still lets me run the solution locally or on my own cloud instance. Deliverables 1. A script or lightweight application (CLI or basic GUI) that performs the three tasks above. 2. Fu...

...helps farmers monitor crop health and estimate likely yields. My immediate focus is on two functions: • Disease detection – flag visible leaf symptoms from the images I already have. • Yield prediction – provide a first-pass estimate based on those same images. Only images of crops are available right now, so the solution should rely on computer-vision techniques (Python with TensorFlow or PyTorch is fine). I need: 1. A well-commented notebook or script that trains and tests both models on my dataset. 2. Clear instructions for retraining with new images. 3. Basic performance metrics (accuracy / F1 or similar) on a held-out sample. 4. A short README outlining next-step recommendations for adding soil, weather, or sensor data as we expand toward irr...

...Rekordbox-compatible metadata. ​Beyond basic tempo and key, the system must leverage Machine Learning models and DSP to automatically calculate deeper sound engineering metrics—sub-bass pressure, full-spectrum RMS density, transient impact, and dynamic punch—and categorize tracks based on acoustic weight and structural energy. ​Scope of Work: ​Develop an autonomous pipeline/script (Python using Librosa/Essentia/PyTorch, or C++/JUCE) that ingests WAV, AIFF, and MP3 files. ​Automatically extract BPM, musical key, and advanced production metrics (sub-bass vs. kick, RMS density, transients, dynamic punch). ​Detect structural shifts (drops, breakdowns, high-energy sections) and calculate macro/micro energy levels automatically. ​Export analysis results into a fully valid R...

...penmanship. What I need from you is an end-to-end solution—from model design to final PDF export—that pairs visual authenticity with solid print fidelity. High-resolution (300 dpi, CMYK-friendly) output is non-negotiable; the pages have to survive a close look after coming off an office laser printer with no tell-tale artifacts. Deliverables • A handwriting synthesis engine (Python, TensorFlow/PyTorch or comparable stack) that ingests text and returns vector or high-resolution PDF files • Style library covering the three handwriting families, built for easy expansion • Configuration interface for all font customisation controls • Documentation plus a short demo video showing the workflow end to end Acceptance criteria Given a 200-word ...

I need an experienced PyTorch/CUDA engineer to squeeze every practical second out of our ROLLCALL Wan 2.2 I2V A14B inference pipeline running on an A100 80 GB while keeping the pictures looking exactly the same. Reducing processing time is the prime objective; any change that simply trades speed for a worse image will be rejected. The first job is a deep profile. Please time each phase separately—model loading, T5/text encoding, VAE, diffusion, decoding, FFmpeg, and all inter-segment overhead—so I can see exactly where the pipeline stalls. From my own sampling it looks as if models may be re-opened for every 5-second chunk, so post-processing and segment overhead are the first areas I’d like you to attack. Once the slow spots are confirmed, create a persistent wa...

...prefers PyTorch as the framework of choice. The immediate goal is to design, train, and fine-tune language models that will power features such as text classification, entity extraction, and semantic search. You should be able to: • architect and code end-to-end pipelines—data ingestion, preprocessing, model training, evaluation, and deployment; • experiment with state-of-the-art transformer architectures, optimise hyperparameters, and benchmark performance on agreed metrics; • containerise and push models to a cloud endpoint (AWS, GCP, or Azure—choose what you know best); • document the approach clearly so the team can reproduce and extend your work. Acceptance criteria for each milestone will include clean, well-commented Python code, r...

...discipline - Required UI & Visualization Tailwind CSS - Utility-first CSS, responsive, data-dense layouts - Preferred Component libraries - Headless / unstyled component primitives (e.g. Radix) - Preferred Data visualization - Charting libraries, dashboards, S-curve and trend charts - Preferred Report generation - PDF, Excel, Word, PowerPoint export - Preferred ML / AI Infrastructure PyTorch & Hugging Face - Model fine-tuning, PEFT/LoRA, Transformers library - Preferred Voice / speech ML - STT, TTS, end-to-end voice pipeline development - Preferred GPU infrastructure - Self-hosted GPU servers, CUDA, resource monitoring - Preferred Inference serving - High-throughput model serving, quantization, optimization - Preferred Evaluation - Standard and custom domain-...

...the entrepreneur’s concept against market demand, cost structures and funding criteria so the final proposal is both realistic and attractive to evaluators. My vision is a cloud-based solution with a simple interface: the user enters location and concept, presses “Generate”, and receives a ready-to-submit application plus an explanatory report. Python, machine-learning libraries (TensorFlow, PyTorch), NLP techniques for grant language, and a lightweight GIS component will likely be needed, but I am open to your preferred stack as long as accuracy and speed remain high. Payment will follow a subscription model of 300 RON per month for five years, aligning our interests over the long term while keeping the service affordable for small businesses. If you have ex...

...Here is what matters most to me: • A well-trained object-detection model tailored to photographic input (no illustrations or charts in the mix). • Consistently higher precision and recall than my existing baseline; lowering false positives is more valuable than sheer speed. • A self-contained script (Python preferred) that can run headless on Linux, making use of familiar libraries such as PyTorch, TensorFlow, or OpenCV—whatever you feel will maximise accuracy. • A concise README that explains installation, inference commands, and how to tweak confidence thresholds. I will supply an initial, labelled photo set for training and a separate, hidden validation set for final evaluation. If your model meets or exceeds the benchmark metrics on that blin...

...Update rankings, metrics, and master files without manual intervention. Required Technical Skills Backend: Advanced Python (FastAPI, Pydantic, asyncio), modular code structuring. Database: MongoDB (pymongo), modeling and optimized queries. Frontend: React, TypeScript, Vite, REST API integration. Automation: Selenium, scraping, authenticated website navigation. Machine Learning: scikit-learn, PyTorch (existing models – no need to create new ones). Infrastructure: Linux, VPS, systemd, Git/GitHub. Plus: Docker, CI/CD, ranking optimization, immutable files, hash validation, stability metrics. Estimated Timeline The system has most of the code written, but nothing has been validated in production. Estimated timeline: 3 to 5 weeks, depending on the professional's ex...

...proven that Wan2.2 A14B can generate usable video on an NVIDIA A100 80GB. The previous prototype used RunPod, Python, PyTorch/CUDA, FastAPI/Uvicorn and FFmpeg, but I do not want to continue patching a fragile experimental environment. The engineer may recommend RunPod, Lambda Cloud, CoreWeave, AWS/GCP/Azure or another appropriate GPU provider, but must justify the choice specifically for a large Wan2.2 A14B workload. Required architecture: ROLLCALL Website → API → Persistent Job Queue/Database → Disposable GPU Worker → Wan2.2 I2V A14B → FFmpeg/QC → Object/Persistent Storage → ROLLCALL Requirements: NVIDIA A100/H100-class production inference Wan2.2 I2V A14B Python/PyTorch/CUDA reproducible Docker-based deployment pinned/compatible de...

I have an operational ERP that runs on a SQL back-end. I now want to unloc...back-testing. 2. Natural-language queries (“Show me yesterday’s top five items”, “Predict next month’s purchase needs”) return results in under five seconds. 3. Scheduled reports (PDF or interactive dashboard) auto-generate and email daily without intervention. 4. Push notifications reach my Android phone instantly when predefined thresholds are met. Preferred stack is Python with TensorFlow/PyTorch and a lightweight API (FastAPI, Flask, or similar), but I’m open to alternatives if they get the job done quickly and reliably. All source code, model artefacts, and setup scripts should be delivered so we can host everything on our own server afterward. Logic ...

...or stereo data (or infer depth with AI) so the user is warned about hazards at cane-length distance or overhead. • Extensible add-ons: hooks for voice commands, emergency SOS, text reading, object recognition, or any future computer-vision module. I already have access to sample hardware (camera-equipped glasses and a tactile band), so you can prototype quickly with OpenCV, TensorFlow Lite, PyTorch Mobile or a stack you prefer. What I really need is the architecture, clean code, and demonstrable logic that meld everything into a smooth UX. Deliverables 1. Source code with clear documentation and build/run instructions 2. A runnable demo (APK, executable, or Web build) that proves indoor & outdoor navigation on my test routes 3. API or module descriptions so mor...

Senior AI Video / GPU Engineer Needed – Wan2.2 + RunPod A100 + PyTorch/CUDA I need an experienced AI/GPU engineer to finish and productionize an existing AI video-generation backend for a platform called ROLLCALL. This is NOT a website design job. The website is already built. I need someone who specializes in GPU inference, Python, PyTorch/CUDA environments, AI video models, and production API deployment. CURRENT SYSTEM We already have: RunPod NVIDIA A100-SXM4 80GB GPU Wan2.2 I2V A14B Approximately 118GB of Wan2.2 model files already downloaded Persistent /workspace storage Python PyTorch/CUDA FastAPI/Uvicorn worker FFmpeg Existing website integration Existing REST API running on port 3010 Current API routes include: GET /v1/health POST /v1/generate GET /...

I’m looking for a **Robotics / AI Engineer** for a short-term research project involving **Vision-Language-Action (VLA) models and robotic manipulation**. ### Required experience * Ubuntu/Linux * ROS 2 * Python / PyTorch * MoveIt 2 and robotic manipulation * VLA/VLM models * Git Experience with **UR5/Universal Robots**, robotics simulation, and implementing recent robotics research papers is strongly preferred. The work will involve integrating an existing VLA approach with a ROS 2 manipulation pipeline, running simulation and real-robot experiments, and documenting reproducible results. This is a focused **few-week engagement** with clearly defined milestones. More information about the research problem, experimental setup, and deliverables will be shared with shortliste...

...as metadata scraping or playlist building can be left as optional notes rather than core components. Here is what I expect from the engagement: • A high-level and component-level architecture diagram showing how audio is ingested, fingerprinted, matched against a reference database, and the result delivered with sub-second latency. • Technology recommendations (e.g., Python, C++, TensorFlow/PyTorch models, audio fingerprint libraries like Chromaprint or ACRCloud SDKs, plus cloud services such as AWS Kinesis, Lambda, DynamoDB, or their GCP/Azure equivalents). • Scaling and fault-tolerance strategy for thousands of concurrent radio channels, including container orchestration (Kubernetes/EKS/GKE) and message queues (Kafka or Pub/Sub). • Latency, accuracy,...

...optimize code for performance and reliability Implement new features to expand functionality or bypass current limitations Test the software thoroughly using provided test accounts Deploy the software to a live or staging environment Provide clear documentation of changes made What We're Looking For: Strong experience with Python (3+ years) Experience working with AI/ML libraries (TensorFlow, PyTorch, Hugging Face, etc.) Proven ability to debug and fix complex codebases Familiarity with GitHub workflows (branching, pull requests, merging) Experience deploying Python applications (Docker, AWS, GCP, or similar) Ability to test software and verify functionality before deployment Strong problem-solving and communication skills How It Works: We provide access to the...

...optimize code for performance and reliability Implement new features to expand functionality or bypass current limitations Test the software thoroughly using provided test accounts Deploy the software to a live or staging environment Provide clear documentation of changes made What We're Looking For: Strong experience with Python (3+ years) Experience working with AI/ML libraries (TensorFlow, PyTorch, Hugging Face, etc.) Proven ability to debug and fix complex codebases Familiarity with GitHub workflows (branching, pull requests, merging) Experience deploying Python applications (Docker, AWS, GCP, or similar) Ability to test software and verify functionality before deployment Strong problem-solving and communication skills How It Works: We provide access to the...

I'm seeking an expert in deep learning and computer vision. You'll work with publicly available datasets to develop an object detection model targeting disease. Key Requirements: - Expertise in PyTorch and Transformers - Proficiency in XAI (Explainable AI) - Strong background in computer vision Ideal Skills and Experience: - Proven experience in building object detection models - Familiarity with relevant publicly available datasets - Ability to explain and interpret model predictions Looking forward to your bids!

...through model deployment—while keeping future scalability in mind. The work involves natural-language processing, machine learning, and solid software-engineering practices. Expect to design a pipeline that cleans and enriches the text, applies state-of-the-art transformers or other suitable models, and exposes the results through a clean API my existing back-end can call in real time. Python, PyTorch or TensorFlow, Hugging Face, and containerisation (Docker/Kubernetes) should feel second nature; if you prefer equivalent tools, I’m open, provided maintainability stays high. Because the insights will feed directly into our live support dashboard, accuracy and low latency are critical. A well-structured test suite, thorough documentation, and CI/CD hooks will be part ...

...Language in real time, turns each recognised sign into clear written text, and then voices that text through natural-sounding speech. The end goal is an easy-to-use educational tool that helps people who are deaf and non-verbal practise everyday communication with hearing users directly from their browser. Scope of work • Build or fine-tune a computer-vision model (e.g., MediaPipe, TensorFlow, PyTorch, or similar) to detect and classify ASL signs from a webcam stream. • Pipe the recognised signs to a text layer, then feed that text into a speech-synthesis engine so the conversation flows naturally. • Develop a responsive web interface where users can sign into the camera, read the live transcript, and hear the spoken output instantly. • Keep latency ...

...repeatable performance on real-world data. The work revolves around text data only. All preprocessing pipelines are in place; the immediate need is to refine the model architecture, tune hyper-parameters, apply efficient training strategies (mixed precision, gradient accumulation, distributed training if helpful), and benchmark the final checkpoints. Familiarity with Hugging Face Transformers, PyTorch or TensorFlow, Weights & Biases, and modern optimization techniques such as learning-rate schedulers, early stopping, and model pruning/quantization will be essential. Deliverables • Fully trained, optimized model files (with version tagging) • Reproducible training scripts/notebooks and environment files • Evaluation report covering metrics, confusion mat...

I ha...images). • Model development: an unsupervised architecture such as auto-encoder, variational auto-encoder, deep clustering, or another approach you can justify for anomaly detection. • Evaluation: quantitative metrics (reconstruction error distributions, AUC, or similar) plus a concise report explaining thresholds and decision logic. • Deliverables: clean, well-commented Python code (ideally PyTorch or TensorFlow/Keras), reproducible environment files, and a short README so I can retrain or fine-tune later. I will supply a representative sample to start; please keep the design modular so it scales once the full dataset arrives. Let me know any additional dependencies you anticipate, along with an outline timeline for data exploration, model iteration, an...

I have a batch of jewellery photos that need an instant lift so they look irresistible online. The sole objective is to increase their visual appeal—think sharper sparkle, true-to-life colour, spotless backgrounds and an overall premium look. You are free to lean on any AI-driven workflow you trust—image enhancement tools such as Topaz Photo AI, Luminar, custom TensorFlow/PyTorch models, or even subtle style-transfer tricks—as long as the final images look clean, consistent and ready for web and catalogue use. Turnaround is critical; I need the finished, high-resolution JPG/PNG files as soon as possible. Please include a brief outline of your process, the number of images you can handle in one pass, and a short before/after sample so I can verify quality.

...can be ignored for now. Accuracy matters more than speed, but the system must still process a typical daily batch (≈10 000 lines) in minutes, not hours. You will receive several months of historically tagged transactions to train and validate the model. I am comfortable with Python and would like well-commented scripts that rely on common libraries such as pandas, scikit-learn, TensorFlow or PyTorch, plus a concise README that lets me reproduce your results on my own machine. Deliverables: • Clean, runnable code (model training + inference) • Trained model weights or checkpoint • README with setup, execution steps, and metrics achieved on the validation set Acceptance criteria: F1-score ≥ 0.90 on the supplied hold-out data and clear, reprodu...

...multi-discipline drawing sets with inconsistent standards Create labeled datasets and continuously improve extraction accuracy Partner with the AI/ML engineer to hand off clean structured data downstream Requirements 4+ years in computer vision or document AI Strong experience with OCR, object/symbol detection, and document layout analysis Proficiency in Python and modern CV/ML frameworks (e.g., PyTorch) Experience with technical or engineering documents, or similarly dense/structured imagery Comfort building data pipelines and annotation workflows...

...market-trend predictions. • Output format: a concise JSON or CSV report with price direction, confidence score and any key indicators you derive. I am comfortable with Python and would prefer to host the solution on a lightweight cloud instance (AWS or similar), but suggest alternatives if they shorten turnaround time. Please include a short note on the framework you plan to use—TensorFlow, PyTorch, or a lighter ML library are all fine as long as they support scheduled retraining. Acceptance criteria 1. An executable script or container that fetches current price data, processes it, and stores the fresh prediction daily. 2. A README that explains setup, scheduling and any environment variables. 3. A quick demo run showing one full cycle from data pull to ...

...variants for premium platforms). Server Hardware & Environment OS: Ubuntu 26.04 LTS CPU: Intel Core Ultra 9 285K (24 Cores / 24 Threads) GPU: NVIDIA GeForce RTX 5090 (32 GB VRAM, Driver 595.84, 575 W power limit) RAM: 60 GB System Memory Storage: 2 TB Samsung 9100 PRO NVMe SSD Key Responsibilities & Scope of Work Server Setup & Stack Configuration: Complete Ubuntu environment setup optimized for PyTorch, CUDA, and high-vram local inference. Deployment and tuning of ComfyUI, Open WebUI, and n8n. AI Character & Video Production Pipeline: Build advanced ComfyUI workflows leveraging SOTA open-source video/image models. Implement character consistency tools using LoRAs and IP-Adapter/ControlNet pipelines. Integrate lip-sync and dialogue tools (e.g., LivePortrait, Mu...

...reproducible code, model versions, prompts, and experiment configurations. * Supporting interpretation of the results and preparation of the AI/methodology sections of the scientific manuscript. Required Technical Skills The ideal candidate should have strong experience in: * Python * Machine Learning / Deep Learning * Large Language Models * Natural Language Processing * Hugging Face Transformers * PyTorch * Local LLM deployment * vLLM or similar inference frameworks * Prompt engineering * Structured JSON generation * Model quantisation * Evaluation of NLP/LLM systems * Data processing with Pandas / NumPy * Git / version control Highly Desirable Experience Preference will be given to candidates with experience in one or more of the following: * Clinical NLP * Medical AI * ...

...Experience with privacy sensitive or client-controlled workflows • Preferred: experience with one of legal, technical, scholarly, or literary corpora. You’ll 1. start by using a corpus I have created of 150 pages, approximately 100,000 words, (it is not chunked or randomized, and if needed, deduplication, train/validation split), then 2. set up the training pipeline with Hugging Face Transformers, PyTorch, and, if helpful, parameter-efficient methods such as LoRA or QLoRA. 3. Once training is complete, I’ll need the model evaluated for factual consistency and style alignment—automatic metrics (perplexity or BLEU) are useful, but a few human-readability samples will help us judge real-world quality. This project requires only one LoRA/QLoRA adapter capturi...

... and document the gains with repeatable benchmarks. • Ongoing maintenance & troubleshooting – create health-checks, monitoring hooks (Prometheus/Grafana preferred), and a rapid-roll-back procedure so downtime is measured in minutes, not hours. Acceptance criteria 1. “nvidia-smi” shows all GPUs at expected PCIe lanes, ECC status and correct clock levels. 2. Training workload provided (PyTorch script, <30 GB) completes at least 15 % faster than the pre-optimization baseline. 3. A markdown run-book details every change and includes upgrade steps for future CUDA releases. Turnaround: I need the first two items finished within the next few days; maintenance scripts can follow immediately after. Access is ready via VPN and IP-KVM. Let me know...

...in Japanese through live online sessions for our platform intellipaat. The audience already has basic programming knowledge, so we will dive quickly into model design, best-practice workflows, and real-world project implementation rather than introductory theory. You should be comfortable switching between conceptual explanations and hands-on coding demonstrations (Python, Jupyter, TensorFlow/PyTorch, scikit-learn). Clear, native-quality Japanese communication is essential; all slides, code comments, and Q&A will be in Japanese. To keep the engagement high I expect: • A concise syllabus that shows how you will sequence ML, DL, and NLP topics over the proposed calendar • Total duration of the course will be 40 hours • Practical assignments after each sess...

I am looking for an experienced Deep Learning / Computer Vision researcher to develop a novel methodology for Image Super-Resolution (SR) based on Implicit Neural Representations (INRs). Strong Python and PyTorch skills. Deep Learning and Computer Vision. Image Super-Resolution. Implicit Neural Representations. Experience implementing research papers. Coordinate-based neural networks. Neural architecture design. Experience with experimental research and ablation studies. Ability to identify research gaps and develop novel deep-learning methodologies.

...take a raw photo—forest, desert, coastline, mountain range, or any other natural scene we decide on—and return the correct label with strong accuracy. Here’s what I need from you: • A well-structured dataset or clear guidance on sourcing and curating one (public sets are fine as long as licensing is respected). • A training workflow in Python using a mainstream framework such as TensorFlow or PyTorch, complete with data-augmentation, fine-tuning, and validation steps. • Trained model weights plus inference code that runs on CPU or GPU with a single command. • A concise README explaining environment setup, training parameters, and how to add new classes later. • Evaluation metrics (precision, recall, confusion matrix) so I can ju...