Hire Neural networks engineers

Building your own neural network in 2024 is actually pretty straightforward for ML engineer with good industry knowledge, as Deep Learning libraries like TensorFlow or PyTorch give engineer pre-built modules for neural network components. All that’s left is to get training data and define network architecture.

Time to train a neural network can differentiate a lot – from few minutes to thousands of hours, depending on a matter of the complexity of your Neural Network architecture, the amount of data you have, and computing power that trains a Neural Network. The simplest models with very good data train very fast on the most powerful hardware, and the large models with less data might take weeks or even months. The answer is broad, and the best way to measure the time to train is actually run training process of your Neural Network.

Neural Networks don’t learn the way humans do. Neural networks do require data, and human guidance, to be trained. Almost all neural networks require the process of training by supervision — for feedback, they take in input and output pairs and learn to map inputs to outputs through iterations.

Development of a Neural network can vary in cost very wide. Depending on the amount of training data, and the target of the project, the cost of computing power to train Neural Network can go from $5,000 up to millions of $USD, where simple models can be trained on your own hardware, whereas Deep Learning models can only be trained efficiently using cloud computing, therefore making the paycheck bigger.

While neural networks are a very powerful tools, they have downsides too. For example, lack of transparency regarding input and output of Neural Network – meaning it’s difficult to trust the network’s decision, especially in the applications where right answer is critical for the end customer, like healthtech or large enterprises. Another downside is the computational cost. Training large neural networks generally requiring a lot of computing power and time, therefore comes the huge cost of computing.
Also, Neural networks typically need a lot of data to train effectively. This can be a challenge if data is limited or expensive to collect.

Yes, neural networks engineers are in demand. The usage of artificial intelligence (AI) and machine learning (ML) has a positive impact on the demand, and the need for professionals skilled in designing, developing, and implementing neural networks is growing. Neural networks developers are working on creating AI models that can perform tasks such as image and speech recognition, natural language processing, autonomous driving, and healthcare diagnostics.

Lemon.io offers a no-risk paid trial period for new clients – the period up to 20 hours, which allow you to check how the developer works on your tasks before signing up for a subscription.

If something goes wrong and the developer fails to meet expectations, we’ll show you another remote developer with our zero-risk replacement guarantee.

To find the right Neural Networks Engineer, you can use different platforms and websites focused on publishing job listings for various companies. You can use websites such as Indeed, Glassdoor, Dice, and Monster. These websites are globally used and very popular in the IT community. You can also check different websites that are targeted at the local hiring market—please check the websites commonly used in your region. The next step is to create the company’s description, list the requirements, add the job listings to the websites, and complete the payments on them. After posting the job listings on different websites, you need to review the CVs and contact relevant candidates. You need to conduct screening calls with them and hard skills interviews, creating relevant questions for the interviews, including technical questions. If you find a candidate who is perfect for the position, you can sign the contract with them. Otherwise, you can use a shorter and more convenient way—ask Lemon.io for help and get relevant CVs of the candidates in 48 hours. All of them will be ready to proceed with the tasks because they are pre-screened—this means that we already did the work for you by checking their CVs and conducting screening calls and hard skills interviews with them.

Lemon.io offers a no-risk paid trial period for new clients – the period up to 20 hours, which allow you to check how the developer works on your tasks before signing up for a subscription.

If something goes wrong and the developer fails to meet expectations, we’ll show you another remote developer with our zero-risk replacement guarantee.