Work with PyTorch specialists who move past basic training to deliver real AI breakthroughs, using clean, Python-first design. From rapid research prototypes to going-live, keep models fast, adaptable, and ready for large workloads.
Hire PyTorch developers who move fast through experimentation, resolve hard-to-debug model challenges, and expand what deep learning can deliver in production. Built for teams that expect research flexibility and production momentum to coexist.
From custom dataset creation and tensor manipulation to model quantization and mobile deployment, our experts take ownership of your entire PyTorch journey.
Hire senior PyTorch developers craft complex architectures (CNNs, RNNs, Transformers) using PyTorch’s intuitive API to support unstructured data analysis like vision and audio.
Hire PyTorch developers to bridge the gap between research and production. We utilize TorchServe and ONNX Runtime to deploy models efficiently on cloud servers or edge devices.
Get the right talent for your specific needs. Whether you need a Deep Learning Researcher for algorithms or an AI Engineer for optimization, we provide flexible options.
Drive sustained inference speed through quantization, pruning, and distributed training on multi-GPU clusters.
Hire PyTorch developers with hands-on skills in Python, CUDA, and distributed computing. Entrans provides top-tier professionals to build, configure, and scale your AI solutions.
Our team builds visual intelligence. Hire PyTorch developers to leverage TorchVision for object detection, image segmentation, and facial recognition systems that operate in real-time.
Hire PyTorch developers to process complex text data. We utilize TorchText and Hugging Face Transformers to build sentiment analysis tools, chatbots, and language translation engines.
Our experts build creative AI. Hire PyTorch developers to implement Generative Adversarial Networks (GANs) and Diffusion models for synthetic data generation and image synthesis.
We execute rigorous validation cycles. Hire PyTorch developers to utilize PyTorch’s native debugging capabilities and TensorBoard for visualization, ensuring models converge correctly and perform reliably.
Entrans’ PyTorch developers manage lightweight deployments. We use PyTorch Mobile to run optimized models directly on iOS and Android devices without relying on cloud connectivity.
We translate papers to code. Hire PyTorch developers skilled in implementing the latest academic research papers into functional, proprietary business algorithms.
Technical Stack: Next.js (SSG), Strapi, Tailwind CSS, Vercel
A leading Fintech services company was limited by its slow, monolithic WordPress site, which hurt its SEO and content workflow. We migrated them to a headless architecture with Next.js for Static Site Generation and Strapi as the CMS.
The new platform had better functionality and a better UX for users uploading bills, statements, and receipts for reconciliation.
Technical Stack: Python, Flutter, Angular, LangChain, FastAPI
Enterprises needed a secure AI solution for human-like conversations grounded in their own proprietary data. We developed Thunai, our enterprise-grade agentic platform, to automate sales and support workflows.
Thunai delivers accurate, data-driven responses, handles complex agent tasks, and provides a unified support experience in over 150 languages.
Entrans provides specialized PyTorch development teams that ensure code readability, training efficiency, and seamless deployment. Our pre-vetted network offers deep expertise in dynamic graphs, autograd, and distributed training, delivered through adaptive engagement models that integrate seamlessly with your existing data science teams.
Identify high-impact AI use cases and datasets that need PyTorch Engineer roles.
Access pre-screened profiles with verified experience in Deep Learning and PyTorch ecosystem contribution.
Validate expertise in Custom Layers, Loss Functions, and Backpropagation through rigorous technical challenges.
Onboard experts who understand your GPU infrastructure and data pipelines, preventing ramp-up delays.
Maintain continuity with structured upskilling on the latest PyTorch versions (2.0+) and compilation techniques.
Ideal for long-term R&D projects and continuous AI product evolution.
Scale your AI team with skilled PyTorch engineers as an extension of your workforce.
Hire for specific tasks, such as model conversion to ONNX, algorithm implementation, or performance tuning.
Our team serves global clientele, specializing in Healthcare, Automotive (Autonomous Driving), and Finance. Our specialists architect intelligent solutions using their deep knowledge of the PyTorch framework.
A PyTorch developer is an AI specialist skilled in using the PyTorch open-source machine learning library. They build, train, and deploy deep learning models for applications like computer vision and NLP using Python.
PyTorch is the dominant framework for rapid prototyping and research, featuring a dynamic computational graph that allows engineers to debug code and iterate on complex models significantly faster. Experts in this framework grant you access to a massive ecosystem of tools.
They design neural network architectures, write custom training loops, optimize hyperparameters, manage tensor operations, and deploy models using tools like TorchServe or ONNX.
Tesla primarily uses PyTorch for training the deep neural networks that power its Autopilot and Full Self-Driving (FSD) systems. They famously transitioned their massive training clusters from other frameworks to PyTorch to handle the extreme scale of their video data.
In the US, hiring a PyTorch developer costs between $130,000 and $210,000 annually, with senior roles in AI hubs exceeding $250,000. Offshore talent offers significant savings, with rates in Eastern Europe averaging $40–$80 per hour and Indian developers charging approximately $25–$50 per hour.