Our tech talent network consists of hundreds of on-site developers, off-site collaborators and top software houses. We will pick TensorFlow superstars perfectly fitted for your product, industry and company culture.
Our goal is not to simply deliver the project. We will help you build a hypergrowth environment around your technology and your product.
Even the best alghoritms are just a part of success. We will provide you with interdisciplinary team of tech business talents, from project managers and strategy consultants to sales and marketing experts.
We take the best principles of agile approach to software development and expand it to other project's areas, to ensure the highest efficiency and transparency of our expert's work.
Our project manager had things taken care of and their backend developers had great technical abilities. They’ve been the best we’ve had so far!View the case study
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Make full use of deep learning faster with the help of TensorFlow. The library supports distributed training across multiple machines, meaning it can get the results you need faster.
Get first results shortly before assembling your deep learning team. TensorFlow makes it easier to build initial algorithms thanks to the vast number of available pre-built functionalities.
Choose a solution that has already proven to be successful across industries. TensorFlow is present in the toolstacks of multiple global IT players, including NVIDIA, Twitter, Uber, and Snapchat.
Make your machine learning algorithms free of bugs and common human errors so the results stay reliable. TensorFlow has multiple functionalities included that allow for easier debugging and keeping your deep learning working issue-free.
TensorFlow is an open-source library for machine learning projects. Although TensorFlow developers use Python to write the code, it’s later translated by the tool into C++ for best performance. The library has been developed since 2015 by the Google Brain Team, with TensorFlow 2.0 released in the fall of 2019.
But why would you need TensorFlow and TensorFlow developers at your company? What are the pros of using machine learning in your business? And, finally, if you decide to hire TensorFlow developers, how to find the ones that will really fit your company and get the job done smoothly?
You will find answers to all of these questions in our ultimate guide below.
The goal of machine learning is to build algorithms that are able to learn and develop their skills autonomously. This is one of the most important steps to automating multiple routine tasks that would normally be done by humans. The final outcome is having the task done more efficiently — faster and with the quality close enough to what humans could achieve.
TensorFlow provides an end-to-end solution for building machine learning models. These models can help your business with:
Being a machine learning expert requires exceptional ability to combine theoretical knowledge with fully technical, engineering skills. The must-have skillset of TensorFlow developers, therefore, includes…
To deliver stable and well-functioning machine learning models. soft skills are nearly as important for a TensorFlow developer as the hard, technical knowledge. They guarantee not only a great product to be developed, but also a feeling of cooperation and helpfulness within the company, which powers the innovation.
The most important soft skills for a TensorFlow expert are…
Like most data scientists, TensorFlow developers are more often university-educated rather than self-taught. Thanks to such professional education, they are not only more motivated to learn more about the technology but are also more knowledgeable of multiple best practices introduced to them by professors and other experts in the field.
TensorFlow developers most often hold a degree in computer science, mathematics, physics, or other fields where higher-level math and algorithm writing is common. Some of the TensorFlow experts also wish to prove their skills by acquiring the official TensorFlow development certificate. As it has been introduced in Google just in 2020, bear in mind that there is still a limited number of TensorFlow developers who received it.
When hiring a TensorFlow developer, you should also consider how their previous experience matches your company’s specific needs. Think especially about the area of machine learning you want them to work on. A TensorFlow developer who spent the last a couple of years perfecting an image processing machine learning model will be a great choice if you also want to automate image classification at your company. However, if you are looking to, let’s say, improve the cybersecurity scans for the clients of your fintech business, you should rather look for devs specialized in this specific area of machine learning implementation.
To properly assess the skills of your candidates for the TensorFlow developer role, a technical job interview is required. If you are not a data scientist yourself, you might want to ask one to join you during the interview to help you ask the right questions. An IT project manager or software consultant with data science focus could also be of help.
What are some of the questions that could be asked during such a job interview? Here are some of our favorites…
To make the most out of machine learning, you will need more than just TensorFlow developers. Additional data scientists, data engineers, and GAN experts might be needed to get the exact results you want.
Thankfully, there is now a way to hire all of these data professionals fast. At Ideamotive, we run a unique network of top IT talents looking for new job opportunities, including a wide range of data experts. What’s more, we connect you only with the people that really fit your company and project to make sure your team cooperates well and delivers results efficiently.
Get in touch with us today and build an amazing data team.
Execute your vision with trusted and battle-tested TensorFlow developers perfectly suited to your business needs.