
Sentiment Analysis
Determining the emotion expressed in text, such as positive, negative, or neutral.
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NLP Developer
9+ years experience • Full-time availability
Verified Skills
Other Skills
NLP Developer
9+ years experience • Full-time availability
Verified Skills
Other Skills
NLP Developer
6+ years experience • Full-time availability
Verified Skills
Other Skills
NLP Developer
3+ years experience • Full-time availability
Verified Skills
Other Skills
NLP Developer
5+ years experience • Full-time availability
Verified Skills
Other Skills
NLP Developer
7+ years experience • Full-time availability
Verified Skills
Other Skills
From food to FinTech, thousands of companies use Supersourcing to hire, scale and grow faster.
Determining the emotion expressed in text, such as positive, negative, or neutral.
Categorizing text into predefined categories, such as spam filtering or news categorization.
Identifying named entities in text, such as people, organizations, and locations.
Translating text from one language to another, such as English to Spanish.
Answering questions posed in natural language, such as answering questions about a specific topic or entity.
Developing conversational agents that can interact with users in natural language, such as customer service chatbots.
The entire process takes around 2-10 days. A clear job description and fast interview turnarounds can reduce this duration.
Supersourcing takes the responsibility of managing employees timesheet, availability. One Senior Account manager will be assigned to each project. We don't prefer bot on support. Our senior team is available even in weekends to support you in your business. Just an Email/WhatsApp away.
Firstly, we understand their technical knowledge through Mettl & HackerEarth. Secondly, we manually verify all data points through different sources to ensure the highest quality of talent.
We don't work with freelancers. We work with developers who are looking for full-time work but at different organisations. The verification interview is also done to ensure seamless compatibility with different companies.
Monthly to yearly, we have different options that companies can choose from.
We assign every company an account manager. Please do reach out to your point of contact to add and remove developers as per requirement.
Yes you can hire them on permanent basis, after 6 months of contact pay one fixed finding fees and hire them on your payroll, Try before you buy. We are really flexible depends on your need.
We recently started in Metro cities in India and Globally; Check with sales team for feasibility! So far we deployed only 700 engineers at location.
Supersourcing will match you with senior developers that fit your JD within 5 days. Sometimes, our expert team can match profiles in even less than a day.
Other Platforms Vs Supersourcing
Multiple Job Boards
You sign-up & subscribe to multiple job boards.
Intelligent Hiring Platform
You sign-up & share your JD highlighting skills, experience, responsibilities.
Wasting Time Interviewing Unskilled Talent
Scouring through multiple resumes & interviewing multiple candidates, wasting time & resources.
AI will Find the Best 5 Matches
100% Profile Matching ensures you need only one round of interview to select the best among the 5.
Waiting for Acceptance
Once you send the offer letter, there is no guarantee that they will accept, delaying your project.
Get Started Immediately
Team Supersourcing will take care of onboarding, timesheets, productivity reports, & post-hiring support.
Traditional Sourcing- Hiring is Slow, Costly & Risky
Time Spent
30 Days
Hiring Cost
$30,000+
Supersourcing - Tech-Driven, Risk-Free, Futuristic
Less than a week
5
Days
Zero upfront cost
$0
NLP Developers
Natural Language Processing (NLP) is a field of computer science and artificial intelligence that deals with the interaction between computers and humans using natural language. The goal of NLP is to develop algorithms and models that can understand and generate human language. This involves tasks such as text classification, sentiment analysis, machine translation, and question-answering systems. NLP draws on linguistics, computer science, and information science to analyze, understand, and generate human language. It has numerous practical applications, including chatbots, virtual assistants, and content moderation, among others. NLP is an interdisciplinary field that continues to evolve and grow as technology advances and the demand for human-like communication with computers increases.
The future of NLP looks promising, with continued advancements in the field leading to more advanced and sophisticated language processing technologies. Some of the future trends in NLP include:
Deep learning has shown great success in NLP tasks, and its use is expected to increase in the future.
NLP models will continue to improve in their ability to generate coherent and natural language.
NLP will increasingly be integrated with other technologies such as robotics, internet of things, and blockchain.
As NLP becomes more prevalent, there will be a greater emphasis on ensuring that these technologies are developed and used ethically.
NLP will continue to expand into new languages and domains, making it accessible to a wider audience.
Overall, the future of NLP is exciting and holds immense potential for improving human-computer interaction and making information more accessible to everyone.
In 2023, NLP is expected to see continued advancements and growth. Some of the developments we might see in NLP this year include:
NLP models will become more human-like in their ability to understand and respond to natural language.
NLP models will continue to improve in their ability to understand and generate text in multiple languages.
NLP models will leverage transfer learning to improve their performance on new tasks with limited data.
NLP will continue to expand into new industries, such as healthcare and finance, to improve efficiency and decision-making.
NLP models will continue to improve in their ability to generate text that is coherent, natural, and informative.
Overall, NLP in 2023 will continue to play a major role in shaping the future of human-computer interaction and information access.
When you hire NLP developers it can bring a wide range of benefits to a company, helping it stay ahead of the competition and improve customer engagement and efficiency. There are several reasons why a company might want to hire NLP developers:
NLP developers can help build advanced applications that can process, understand, and generate human language.
NLP developers can help build conversational AI systems that can improve customer engagement and provide a more human-like experience.
NLP developers can help extract insights from large volumes of unstructured data, such as customer reviews or social media posts.
NLP developers can help automate manual tasks, such as content moderation or sentiment analysis, to improve efficiency and accuracy.
Companies that invest in NLP technology will have a competitive advantage over those that don't, as they will be able to offer more advanced language-based services and applications.
NLP developers play a crucial role in the development and implementation of NLP systems and applications. They are responsible for ensuring that these systems are accurate, efficient, and meet the needs of the business and its customers. The responsibilities of NLP developers vary depending on the specific role and company, but some common tasks include:
NLP developers are responsible for designing and implementing algorithms and models that can process and understand human language.
NLP developers are responsible for continuously improving existing NLP systems to make them more accurate and efficient.
NLP developers are responsible for preprocessing and cleaning data to ensure that it is suitable for NLP models.
NLP developers are responsible for evaluating NLP models to ensure that they are performing well and meeting the desired accuracy and efficiency requirements.
NLP developers often work closely with other teams, such as data scientists, product managers, and designers, to ensure that NLP systems meet business requirements and deliver value to customers.
An NLP developer should have a strong technical background, a deep understanding of NLP concepts, and the ability to work effectively in teams and communicate complex technical concepts. An NLP developer should have a strong skill set in the following areas:
NLP developers should be proficient in programming languages such as Python and have experience with NLP libraries and frameworks such as NLTK, spaCy, and PyTorch.
NLP developers should have a deep understanding of NLP concepts, such as text classification, sentiment analysis, and machine translation.
NLP developers should have experience preprocessing and cleaning data to ensure that it is suitable for NLP models.
NLP developers should have a strong understanding of deep learning concepts and be proficient in using deep learning frameworks such as TensorFlow and PyTorch.
NLP developers should be able to work effectively in teams and communicate technical concepts to non-technical stakeholders.
NLP developers should be able to analyze complex problems, identify solutions, and implement them effectively.
Here are some common questions and answers related to hiring NLP developers:
The average salary of an NLP developer varies depending on location, experience, and company size, but in the United States, it can range from $90,000 to $150,000 per year.
A bachelor's or master's degree in computer science, artificial intelligence, or a related field is typically required for NLP development. However, some NLP developers have self-taught skills and may have a different educational background.
Experience in NLP development is typically required, including experience with NLP libraries and frameworks, deep learning, and data preprocessing and cleaning.
The most important skills for an NLP developer include strong programming skills, a deep understanding of NLP concepts, experience with deep learning, and the ability to work effectively in teams and communicate complex technical concepts.
The hiring process for NLP developers typically includes a review of the candidate's resume and portfolio, technical skills assessments, and one or more rounds of interviews with the technical and non-technical teams.