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How to hire TensorFlow developers with Ideamotive?

Hire TensorFlow Developers

Tell us about your business requirements

Talk to our advisor about your exact needs, product specifics, and team dynamics. The more we know at this step, the better the future match will be.

Get the shortlist of talent under 24 hours

Based on the interview, we will shortlist TensorFlow Developers best suited for your needs.

Hire and onboard with a money-back guarantee

We will onboard the talent and take care of all payments, insurance, reporting, and other dull processes. There is also a 7 days money-back guarantee after the project's kick-off.

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Leverage The Full Power Of TensorFlow

Get results faster

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.

Build algorithms with ease

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.

Standardize your operations

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.

Avoid costly mistakes

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.

How To Hire a TensorFlow Developer and What Skills To Look For?

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.

Why hire a TensorFlow expert?

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:

  1. Image recognition and image classification
  2. Natural language processing (NLP)
  3. Forecasting based on data
  4. Automating customer service with chatbots
  5. Calculating risk which helps in making data-driven decisions
  6. Improving marketing by tailoring ads to specific clients
  7. Spam filtering
  8. Detecting fraud and other cybersecurity breaches
  9. Building the AI for self-driving cars and other autonomous devices
  10. Automating data tagging

TensorFlow developer hard skills

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…

  1. Machine learning knowledge

    Including understanding of different approaches to machine learning, e.g. supervised and unsupervised ML, as well as of other data science-related concepts, including AI and deep learning.

  2. Understanding of complex mathematics

    A must for working with machine learning. Complex mathematics, in this case, covers areas like probability and algorithms.

  3. Vast experience with TensorFlow

    This might sound obvious, but be aware that not all machine learning engineers are experienced specifically in the TensorFlow development environment, but might still apply for the position. Focus on these candidates who actually have experience with TensorFlow (and its additional libraries and extensions) so you can be sure they can start working on your project right away.

  4. Proficiency in Keras

    Keras is a Python neural network library. It can be used on top of TensorFlow to expand on the features present in the vanilla TF. For the best performance and reliability of your machine learning models, using Keras is highly recommended, so make sure that the candidate you choose has already worked with this library.

  5. Knowledge of Python from a data scientist perspective

    As all the coding in the TensorFlow development environment is done with Python, knowledge of this programming language is a must for your candidates. Make sure their Python experience is strictly linked to machine learning with TensorFlow — being a Python web or software developer doesn’t mean they also know how to handle machine learning with the language.

  6. Additional technological knowledge

    Although this is usually not required, it’s a great advantage for your business anyway if your TensorFlow developers have also experience with other machine learning environments. These could be Python alternatives to TF (e.g. PyTorch, Caffe) and/or additional programming languages often used for machine learning, like C++ or R.

Most important soft skills of TensorFlow developers

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…

  1. Patience

    Patience is crucial especially for being ready for all the crashes, bugs, and other issues that might happen with an ML model. Attention to detail and double-checking every line of code is a must in the role of a TensorFlow developer.

  2. Curiosity

    Machine learning is still an area of expertise that can be innovated and reoriented. Researcher attitude, desire to learn new things, is crucial for TensorFlow experts as it encourages them to look for new ways of doing things and improving their models every step of the way.

  3. Pro-business attitude

    Pro-business attitude guarantees your developers always think of the company’s goals when experimenting with new features and tailor their development process to the current business needs.

  4. Approachability

    TensorFlow is not a lone wolf, but a part of a bigger machine learning/data science team. Great cooperation between each member of this team is the key to delivering amazing data-based results.

The educational background of TensorFlow experts

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.

Assessing the experience of TensorFlow developers

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.

Top TensorFlow developer job interview questions

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…

  1. What is TensorFlow Serving used for?
  2. What is naïve Bayes and why is it called „naïve”?
  3. How to overcome Curse of Dimensionality?
  4. What is batch normalization?
  5. What is convex hull?
  6. How is the k-nearest neighbor algorithm different from k-means clustering?
  7. When is stratified cross-validation used?
  8. How to combat imbalanced dataset?
  9. Why is feature selection considered necessary?
  10. What is the difference between fixed-width binning and adaptive binning?

Who else will you need for your data team?

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.

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