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Build stunningly performing machine learning models in a short time. PyTorch is an incredibly user-friendly tool, allowing developers to deliver results fast.
Get machine learning models that deliver reliable outcomes. PyTorch can utilize GPU acceleration to truly power up your market forecasting.
Utilize the support provided for PyTorch by its developers. The tool has been built by data experts at Facebook and is used by companies like Uber and Tesla.
Automate and cut costs across all parts of your business. PyTorch is a versatile tool that can be utilized for all types of ML models, from forecasting to NLP.
Even in the ever-changing world of machine learning, PyTorch is considered a new technology. Developed by Facebook's AI Research lab, this ML library has been initially released in 2016, but the 1.0 launch came in late 2018. To many people’s surprise, the tool quickly gained traction and rose to be one of the most broadly used machine learning solutions.
In 2018, when the 1.0 released, PyTorch was still used by a minority of researchers — but 2019 suddenly brought it to the top. The trend began in academia but PyTorch quickly found its place in the world of business as well. Now, PyTorch is the core of some of the major deep learning solutions on the market, including Tesla Autopilot and Uber's probabilistic programming language Pyro.
In our guide below, we explain how PyTorch can be useful for companies across all industries as well as how to hire PyTorch developers who can build and maintain reliable and amazingly performing machine learning models.
The clue of machine learning is right there in the term itself — the goal is to build models that allow computers (machines) to autonomously learn and develop their skills. Developers can give a machine a specific goal to be achieved and feed it with terabytes of data, but the rest is to be done by the computer.
While it may take some time to develop a reliable machine learning model for your company’s needs, the outcome is worth it — a machine can handle routine tasks normally done by humans, but do them more efficiently, saving you both time and money.
PyTorch can be used to develop a variety of machine learning solutions and guarantee their top performance (for example, by utilizing GPU). Companies worldwide hire PyTorch developers to build models that help them with:
As machine learning and PyTorch are the answers to so many different problems, it shouldn’t be a surprise that the technology is now used by both huge and very small businesses alike. The number of PyTorch developers is also growing — according to the 2020 Stack Overflow Developer Survey, currently, approximately 4.1% of professional developers use PyTorch in their work. To help you navigate the market and hire PyTorch developers who truly can get the job done, we dedicate the rest of our piece solely to the hiring process.
As a highly complex specialty, machine learning with PyTorch requires a set of very specific technical skills. We list the most important ones below.
While all the above technical skills are surely a must for a PyTorch developer, you should not ignore the power of soft skills either. They can significantly improve how well your whole data/machine learning team operates and lead to even better results.
When you hire PyTorch developers, look especially for candidates with the following soft skills…
It shouldn’t be a surprise that PyTorch became a huge thing first in the world of research. Universities across the world are deeply involved in the machine learning revolution and give students the chance to learn more about the new technology by themselves.
When you hire PyTorch developers, you should preferably be looking for professionals with a degree that proves their understanding of the field. PyTorch developers are often graduates in computer science, mathematics, physics, statistics, or other similar fields. Many hold at least a Master’s degree.
But you shouldn’t measure your candidates only by their degrees. Business experience is as much — or possibly even more — important.
Make sure to hire PyTorch developers who have previously worked with machine learning in a business environment. The worlds of university research and commercial ML are very different and it’s important for your new hire to be already knowledgable about these differences. You will then avoid any misunderstanding and make sure the person you hire won’t leave you after hitting the first obstacle.
Remember also to focus on PyTorch developers who are specialized in the machine learning solutions you are specifically looking for. If your focus is natural language processing, you should hire PyTorch developers experienced in this unique area, and not those working primarily on forecasting.
As machine learning with PyTorch is a highly specialized field, remember that technical job interviews for your candidates should be run by a true ML expert. If you are not one yourself, you can ask for assistance from other machine learning engineers or a software consultant/IT project manager who is deeply involved in the world of data.
Below we list examples of popular PyTorch job interview questions to give you an idea of how such an interview may look like.
Hiring PyTorch developers is a great starting point for taking your company into the future. If you want to leverage the power of data even more, you should also consider hiring other specialists in the field, such as AI experts, TensorFlow developers, data scientists (including data engineers), or GAN experts.
And whoever you are currently looking for, Ideamotive can deliver. We run an industry-leading network of IT specialists from all fields, including machine learning. Whether you need to start up your business with amazing web or mobile developers or power up your enterprise with talented machine learning engineers, we can connect you with professionals perfectly matching your unique requirements.
Execute your vision with trusted and battle-tested Pytorch developers perfectly suited to your business needs.