We Help You Hire an NLP Developer From South America
Hiring an NLP (Natural Language Processing) Developer from an offshore or nearshore company can often be confusing and time-consuming. To be the best NLP developer for your role, you must be smart, responsible, and hardworking, as well as possess verified skills and experience in NLP.
Our custom AI matching algorithm helps you find the perfect developer for your project. By combining data analysis with personal interviews, we find an excellent match for your team.
We want to help you hire an NLP developer who will contribute quality code from day one. Several fast-growing startups trust our hiring process because it has been refined over several years. Working with us, you can feel assured your hiring a verified professional when you hire your next NLP Developer.
Work to USA Hours
Since our NLP developers are in Brazil, they are happy to work US hours to be able to communicate with your already existing team.
South American Prices
South American software developers who are eager to work with US companies have joined our team.
No Surprise Extra Costs
Our company handles personnel benefits, local employment taxes, and other employment-related expenses.
Vetted Professional NLP Developers
You can be assured you are hiring a skilled NLP Developer who has gone through our rigorous testing process when you hire a software developer with us.
Testimonials
What is NLP Development?
NLP (Natural Language Processing) development refers to the creation and implementation of software systems that can understand, interpret, and generate human language. It involves using computational algorithms and techniques to process, analyze, and manipulate textual data, enabling machines to interact with human language in a meaningful way. NLP development encompasses a wide range of applications and techniques that leverage language data to address various business needs.
Sentiment Analysis and Opinion Mining
NLP development is employed to perform sentiment analysis and opinion mining, which involves extracting subjective information from text data. By analyzing sentiments expressed in customer reviews, social media posts, or surveys, businesses can gain insights into customer satisfaction, public opinion, and brand perception. This information can drive decision-making processes, reputation management, and product improvements.
Language Translation and Localization
NLP development plays a crucial role in language translation and localization. Machine translation models built by NLP developers enable the automatic translation of text from one language to another, facilitating cross-lingual communication and global accessibility. Localization efforts, such as adapting software interfaces or content to specific cultural and linguistic contexts, also rely on NLP techniques to ensure accuracy and linguistic fluency.
Text Summarization and Information Extraction
NLP development involves creating algorithms and systems that can automatically summarize and extract relevant information from large volumes of text data. Text summarization techniques condense lengthy documents or articles into concise summaries, enabling users to quickly grasp the main points. Information extraction methods help in extracting structured data from unstructured text, such as extracting key details from news articles or extracting product attributes from e-commerce descriptions.
A Wide Range of Business Applications
NLP development encompasses a wide range of applications, including sentiment analysis, language translation, and text summarization. By leveraging NLP techniques, businesses can gain insights from language data, overcome language barriers, and extract valuable information from textual sources, ultimately enhancing decision-making, communication, and user experiences.
Why hire an NLP Developer?
Hiring an NLP (Natural Language Processing) developer can bring significant advantages to tech companies. NLP developers possess specialized skills and expertise that can be leveraged to unlock the power of language data, enabling businesses to gain valuable insights, enhance user experiences, and automate processes.
Advanced Text Analysis
NLP developers excel in developing algorithms and models to analyze and interpret human language. They can extract meaning, sentiment, and context from unstructured text data, allowing businesses to gain actionable insights from vast amounts of textual information. This can be invaluable for tasks such as customer feedback analysis, market research, and social media monitoring.
Intelligent Chatbots and Virtual Assistants
NLP developers can design and build intelligent chatbots and virtual assistants that can understand and respond to human language in a natural and conversational manner. These applications can provide instant customer support, handle inquiries, and automate repetitive tasks, enhancing customer satisfaction and improving operational efficiency.
Language-based Recommendations and Personalization
By hiring NLP developers, tech companies can develop recommendation systems and personalized experiences based on language data. NLP algorithms can analyze user preferences, behavior, and contextual information to deliver tailored recommendations for products, content, or services. This capability can significantly enhance user engagement, increase conversions, and drive customer loyalty.
NLP Empowering Tech Companies
Hiring an NLP developer empowers tech companies to harness the power of language data. From advanced text analysis to intelligent chatbots and personalized
- Sentiment analysis for customer feedback.
- Chatbot for customer support automation.
- Text classification for content categorization.
- Named entity recognition for information extraction.
- Speech recognition for voice-to-text conversion.
- Machine translation for multilingual communication.
- Topic modeling for content understanding.
- Text generation for personalized recommendations.
Claúdio Costa
NLP Developer
8+ Years of AI 7+ Years of NLP Development. Enjoys working on language problems
André Dias
Sr NLP Developer
12+ Years of Python 8+ Years of NLP development. Lots of experience in the financial industry and banking
Nilton do Nascimento
NLP Engineer
10+ Years of Data Science 8+ Years of Language model development. Previously worked for a number of AI tech companies.
What does an NLP Developer do?
An NLP Developer leverages Natural Language Processing (NLP) techniques to enable machines to understand and interpret human language. They work on designing and implementing algorithms that allow computers to process and understand human language. They also develop and maintain systems that employ these algorithms for applications like chatbots, voice assistants, sentiment analysis, and machine translation.
NLP Developers work closely with Machine Learning Engineers and Data Scientists to fine-tune these systems based on the results of rigorous testing. They also collaborate with other teams in the company, such as the UI/UX team, to ensure that the final product provides a seamless and intuitive user experience.
In addition, they stay updated with recent advancements in NLP and machine learning and incorporate them into their work. They play a crucial role in bridging the gap between machines and human language, thereby enhancing the value of services that the company offers to its customers.
A Reliable NLP Development Partner For You
Developing NLP apps and backend systems requires an experienced and reliable partner in the field. Our goal is to provide a premium and professional service to all our customers. Get your NLP development team off to a great start, by contacting us today!
How to Hire an NLP Developer?
Here are three steps you can follow in order to hire an NLP developer with us:
Click the button below and fill in your requirements and click send. Please provide information about what your specific NLP needs are and a description of your project.
Receiving and interviewing resumes from NLP developers. We start preparing a shortlist of professionals to interview once the proposals start coming in from HR.
From what you fill out in the requirements we will determine the scope of work and the specific type of NLP developer you need.
- Project Scope: From language modeling to big data text processing list all the deliverables you’ll require.
- Expected Project length: Your job post should indicate what timescale you expect the work to be completed in or if it is ongoing.
- Industry Background: If you prefer someone with certain industry background, mention this here.
- Preferred Billing: Tell us if you prefer hourly rates or monthly bills.
How much does it cost to Hire an NLP Developer?
It is common for many factors to have an impact on the cost, such as expertise, experience, location, and market conditions.
NLP Developers who have lots of experience will also deliver higher-quality results, work faster, and have more specialized areas of expertise in addition to commanding higher fees.
A beginner will price their NLP development services lower as they gain experience.
The hourly rates for our South American NLP developers are:
Junior
Prices From- Works to U.S time zones
- No Recruitment Fees
- Vetted Skills & Experience
- Fulltime Working for you
- No Unreliable Freelancers
Intermediate
Prices From- Works to U.S time zones
- No Recruitment Fees
- Vetted Skills & Experience
- Fulltime Working for you
- No Unreliable Freelancers
Senior
Prices From- Works to U.S time zones
- No Recruitment Fees
- Vetted Skills & Experience
- Fulltime Working for you
- No Unreliable Freelancers
With us, you can hire an NLP Developer from South America!
Developer prices may vary depending on exact skill and experience requirements and availability.
You’ll have to decide which one works best for your project based on its specifics.
What does NLP code look like?
Natural Language Processing (NLP) code is typically written in high-level programming languages such as Python, leveraging libraries like NLTK (Natural Language Toolkit), Spacy, and others that provide pre-built functionalities for common NLP tasks.
An example of NLP in Python would be performing part-of-speech (POS) tagging using the NLTK library. POS tagging is the process of labeling each word in a sentence with its appropriate part of speech (e.g., noun, verb, adjective, etc.).
import nltk
nltk.download('punkt')
nltk.download('averaged_perceptron_tagger')
text = "Natural Language Processing is fascinating."
words = nltk.word_tokenize(text)
# POS tagging
tagged_words = nltk.pos_tag(words)
print(tagged_words)
This output is a list of tuples, where the first element of each tuple is a word from the sentence, and the second element is the part-of-speech tag. ‘JJ’ stands for adjective, ‘NNP’ for proper noun, ‘VBZ’ for verb (3rd person singular present), ‘VBG’ for verb (gerund or present participle), and ‘.’ for punctuation.
What Interview Questions should you ask an NLP developer before hiring them?
What is your approach to pre-processing text data, and why is it important?
This question assesses the candidate’s understanding of the crucial initial steps in NLP, such as tokenization, stemming, lemmatization, and stop word removal. Their answer will reveal how they handle data cleaning, their familiarity with different techniques, and their ability to justify their choices based on the requirements of the task at hand.
Can you describe a project where you’ve used word embeddings (like Word2Vec or GloVe) and explain their advantages over traditional Bag-of-Words models?
Word embeddings are essential tools in modern NLP. The candidate’s response will indicate their practical experience with these techniques and their understanding of the advantages they offer, such as capturing semantic relationships between words and handling large vocabularies efficiently.
How would you handle ambiguous words or phrases in NLP, and what techniques would you use for disambiguation?
Language ambiguity is a significant challenge in NLP. A candidate’s answer to this question will showcase their knowledge of advanced NLP concepts and techniques like context-based models, named entity recognition, or part-of-speech tagging, and how they can be used to address this challenge.
Do You Enjoy Working Alone or within an NLP development team?
NLP software engineers can have any combination of personal traits, so there is no right or wrong answer to this question. It may be important to you to hire an NLP engineer who is hardworking and can function independently. In contrast, you might want someone who works well with others and isn’t stubborn.
Can you explain the concept of attention in the context of transformer models like BERT or GPT, and why it’s useful?
Transformers have revolutionized NLP in recent years. This question probes the candidate’s understanding of the latest advancements in the field. Their ability to explain the concept of attention—a mechanism that allows models to focus on important parts of the input when processing data—will indicate their familiarity with these cutting-edge techniques and their potential to contribute to advanced NLP projects.
NLP Development History
Natural Language Processing (NLP) is a branch of artificial intelligence that focuses on the interaction between computers and humans through natural language. The goal is to program computers to process large amounts of natural language data. NLP’s history is marked by distinct periods of progress and evolution, punctuated by major breakthroughs that have pushed the field forward.
Early Days of NLP: Rule-Based Systems
In the early stages of NLP, from the 1950s through the 1980s, the focus was on creating rule-based systems. These systems relied on hand-written rules and a linguistic understanding of language, with researchers attempting to codify “rules” of language that the computer could follow. However, the complexity and diversity of human language made it difficult to make significant progress with this approach.
Statistical Revolution: Machine Learning in NLP
The advent of machine learning techniques in the late 1980s and early 1990s revolutionized NLP. Systems were now able to learn rules from data, shifting from rule-based to statistical methods. This period saw the development of algorithms that could analyze language based on the likelihood of a word’s occurrence. Techniques such as Hidden Markov Models and later, neural networks, were employed to create more sophisticated models.
The Future of NLP: Contextual Word Embeddings and Beyond
The future of NLP is likely to be dominated by techniques that can understand the context of words and sentences more accurately. The introduction of transformer models and contextual embeddings, such as BERT and GPT, have significantly improved the performance of NLP tasks. These models can capture the meaning of a word in relation to its surrounding words, leading to a much richer understanding of language. As we move forward, we can expect more advancements in this direction, with increasingly sophisticated models that can understand not just the literal meaning of text, but also its tone, nuance, and context. We also anticipate more integration of NLP with other AI technologies, such as computer vision and reinforcement learning, to build more comprehensive AI systems.
Why are we the best choice to hire an NLP Developer?
As a leading Nearshore Technology Solutions company, we provide an experienced NLP developer at a competitive price. Our goal is to provide our clients with high-performance, scalable solutions.
We provide NLP project acceleration or rescue by utilizing our NLP development prowess and project management experience. Always striving to create lasting value throughout the development of your NLP project and beyond.
Trusted by over a hundred startups and AI tech companies around the world, we’ve matched a hundred skilled NLP developers to great teams.
Our NLP developers become devoted members of your team, fully integrated into your organization.
Every NLP developer we supply goes through a vetting process to verify their communication abilities, remote work readiness, and technical skills (both for depth in natural language processing and programming but also, we check for breadth of knowledge across software development and data science).
Cost Reduction
Companies usually outsource in order to reduce costs. Hiring NLP engineers from outside the United States costs less. You will also significantly reduce overall employment costs. You won’t have to pay US or European employment taxes, benefits, redundancy liabilities, or office space.
Scale Fast
Expanding and downsizing quickly can be a great competitive advantage for any industry. Outsourcing NLP developers with us will allow your business to scale up or down as you need, and with relative ease.
Professional Experience
With NLP development outsourcing, you’re entrusting your project to a company with extensive experience in helping businesses achieve their business goals. As a result, you can feel more secure knowing that your NLP project will be delivered on schedule and within budget.
What can you do with an NLP Developer after you hire them?
After hiring an NLP Developer, they can be tasked with several key responsibilities. They can develop and implement algorithms to process and understand human language, helping to create applications such as chatbots, voice assistants, or automated customer support systems.
An NLP Developer can also work on sentiment analysis, which can be crucial in understanding customer opinions and improving products or services based on customer feedback.
They could also develop machine translation systems to break language barriers and enable better global communication. Furthermore, they can work closely with data scientists to use NLP techniques for data extraction and analysis, helping to make sense of large volumes of unstructured text data.
Finally, they can use the latest advancements in NLP and machine learning, incorporating them into their work to keep your company’s technology at the cutting edge.
- Enhanced customer service with automated support systems.
- Insightful sentiment analysis for improved product development.
- Efficient data extraction from unstructured text.
- Breaking language barriers with machine translation.
- Streamlined internal communication with smart assistants.
- Staying ahead with cutting-edge AI technologies.
How do we code test an NLP Developer before hiring them?
To code test an NLP developer, we give them a test that assesses their ability to perform key NLP tasks. For instance, we may provide a dataset and ask them to preprocess the text data, including tokenizing, removing stop words, and stemming or lemmatization.
We also ask them to design basic machine learning model, such as Naive Bayes, for a simple task like text classification or sentiment analysis. Alternatively, we might ask them to use a pre-trained model like BERT or GPT-2 for a more advanced task.
The evaluation not only focuses on their coding skills, but also on their understanding of NLP concepts, their ability to choose the right approach for a given problem, their knowledge of different NLP libraries and tools, and their ability to interpret and articulate the results of their model.
How do you effectively manage NLP Developers after you hire them?
Managing NLP developers effectively involves understanding their unique needs and challenges. It requires facilitating their work, ensuring they have the necessary resources, and guiding them towards achieving business objectives. Here are five key aspects to consider:
Fostering Collaboration and Communication
Promote a collaborative environment where NLP developers can work with other teams, like data scientists, UI/UX designers, and product managers. Effective communication can facilitate the integration of NLP applications into larger systems and improve overall product development.
Providing Ongoing Training and Development
Keep your NLP developers updated with the latest advancements in the field. Provide opportunities for learning new tools, algorithms, and techniques through training programs or workshops.
Setting Clear Objectives and Expectations
Set clear project goals and performance expectations. NLP developers should understand their role, what they’re working towards, and how their work impacts the overall business objectives.
Ensuring Access to Resources
Make sure developers have access to necessary resources, including powerful computing infrastructure, relevant datasets, and sophisticated development tools. These resources are essential for developing and testing advanced NLP models.
Encouraging Innovation and Experimentation
Support the exploration of innovative ideas and novel solutions. NLP is a rapidly evolving field and encouraging experimentation can lead to breakthroughs that give your company a competitive edge.
How long does the average NLP Developer stay in a job?
After you hire an NLP Developer in the US on average, they stay between 1.6 and 3.1 years in the job, with larger companies tending to keep workers longer. The average time spent in Brazil is between 2.5 and 4.2 years, with those in Sao Paulo spending the least time. In the past, it wasn’t unusual for someone to spend their entire career at one company.
Experienced Senior NLP Developers may transition from job to job fairly quickly, seeking new opportunities and more money, as such longevity is no longer commonplace. With a low unemployment rate and a desperate need for professionals with NLP, AI and other vital skills, the most in-demand NLP pros can migrate between jobs (or even freelancing) fairly easily in this market. Communication with employees is key, and we offer perks to attract and retain top talent.
Frequently Asked Questions (FAQs)
Our services are trusted by hundreds of startups and tech companies worldwide, and we have matched a hundred skilled NLP developers to great development teams in the US, UK and Canada. Every NLP developer in our network goes through a vetting process to verify their communication abilities, remote work readiness, and technical skills, both for depth in Natural Language Processing and breadth across the greater programming domain.
The job description of a NLP Developer should include the following:
Developing, implementing, and managing NLP Solutions
Enhancing existing programs by identifying areas for improvement with NLP
NLP Coding in an efficient manner
Analyzing operational feasibility
Establishing procedures for quality control
Implementing NLP tools, processes, and metrics
Upgrades of existing systems with NLP
Assisting other developers, UX designers, and business analysts with their tasks
It’s not enough to just ship features; your software needs to help your business succeed. In order to better understand what you’re building, for whom, and why, we’ll begin our collaboration with a discovery process.
Our headquarters are in Sao Paulo, Brazil. We have clients from all over the world. We have successfully collaborated with companies in North America, Asia, the Middle East, and Europe. A good understanding of each client and excellent English communication skills help the process run smoothly.
We can work with you to scale the team down as needed and make sure you have the correct skills required for each project phase.
All Types! You can hire an NLP Developer on a full-time, part-time, or contract-to-hire basis at Hire AI Developer. We can find you an NLP developer in a time zone that suits your needs thanks to our global network of skilled Natural language engineers. NLP Developers who work remotely for us are all mid- and senior-level professionals, ready to code right away.
