Hire NLP engineers

Implementing NLP can differ a lot in total paycheck. Simple projects like chatbots can cost a few thousand dollars, while complex systems with deep learning algorithms can go up to millions of USD. Building your own NLP model requires a data science team, making it very expensive. Pre-built solutions are cheaper but might lack some features. Generally, simple NLP projects start from $6,000 and go well over $100,000 for Advanced NLP systems.

Although it is a popular and rising technology, NLP has its pitfalls too. As powerful as it would be, biases can be transferred into an NLP model from its training data to produce rather questionable results. Language is tricky; for example, sarcasm, and cultural references may generally throw NLP systems off track. NLP deals with context badly and requires tons of good data to function well. Another big concern is that of security, hackers might fool NLP systems into generating the wrong or even dangerous outputs. So, while NLP has a lot of opportunities to be used for good causes, people should be aware of its limitations.

Due to its wide range of applications, NLP is gaining more popularity over the past few years. In general, NLP is making the way to revolutionize many areas of human interaction with machines. Coupled with the increased use of AI and big data, strong pre-trained models in NLP have been developed; things as GPT-3 and BERT. Therefore, its application became adopted across every industry.

Yes, NLP is in demand. Voice assistants, chatbots, and language translation technologies are getting easier to use, and NLP has become a skill expected in every industry. This demand has also spawned a new position: the NLP Engineer. Testing new technology, and further increasing its functionality nonstop, places the bar very high for NLP engineers, whose demand seems to be increasing immensely.

Python is the best programming language to utilize for NLP.
Using Python in NLP will generally be suggested because of its simple syntax and semantics, a large number of useful libraries—like NLTK, spaCy, and TensorFlow, with prebuilt functions for many NLP tasks—thereby making the development of an NLP application easier and more straightforward.

In order to hire an NLP engineer, requirements for the project need to be defined first — a list of necessary skills and experience stated. A detailed job description will include what you are looking for, responsibilities, qualifications, and an overview of your company. Creating a job posting on several different platforms like LinkedIn, GlassDoor, Indeed, Dice, specialized tech job boards, and developer communities allows finding a fitting candidate. Screen their resume and portfolio for relevant experience. Then, follow up with technical and behavioral interviews, including coding challenges and code reviews. Check professional references for work history and abilities. Design a competitive offer pertaining to the grade of pay, benefits, etc., followed by easy onboarding with proper orientation and training. Look out for candidates who really fit into your team culture and project needs.

Lemon.io, on the other hand, makes the process much simpler for you: you only need to proceed with 3 steps – discovery call, check the 2-3 CVs of the pre-screened NLP Engineers manually selected for you from the huge developer community, and connect with the right engineer.

Basically, NLP is a sub-field of AI that solves the problem of communication between computers and human language. Meaning it’s the process of programming computers for the processing and analysis of huge reams of data in natural language.
Deep learning is a sub-domain of machine learning that deals with many layers of neural networks. Technically, NLP falls under the broad umbrella of AI. Therefore, NLP is heavily reliant on Machine Learning and, more specifically, Deep Learning techniques to realize its goals.

Duties could be potentially different for NLP developers based on the domain of the industry one would be working in, but basically, NLP developer do develop and design language understanding systems and applications, conditioning on effective text representation techniques.

A NLP developer could have different seniority levels, skill sets, and number of years of experience, so the salary depends on those factors. Usually, the rates for in-house workers and independent contractors are different. The salary of a NLP developer in the US, ranges from $157k to $240k, according to GlassDoor.

You can hire a NLP Engineer through Lemon.io in 48 hours – this time is enough to manually check the relevant NLP Engineers from our community and find the perfect candidate for you. All the candidates who have already joined the community are pre-vetted: it means that our recruiters have already checked their CVs, the candidates have successfully passed the screening calls and tech interviews, and are ready to join the interview with the client.

Lemon.io offers a no-risk paid trial period for new clients – a period up to 20 hours, which allows 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.