Data Scientist – NLP & LLM

Data Scientist – NLP & LLM at NeoGenCode Technologies Pvt Ltd · Gurugram · 4 - 6 years · ₹10L - ₹18L / yr · Raised funding · Posted 19 Jun 2026

Data Scientist – NLP & LLM

at NeoGenCode Technologies Pvt Ltd

Posted by Akshay Patil

4 - 6 yrs

₹10L - ₹18L / yr

Gurugram

Skills

Data Science

Natural Language Processing (NLP)

Large Language Models (LLM)

spaCy

Named-entity recognition

Recurrent neural network (RNN)

Long short-term memory (LSTM)

Transformer

GPT models

Job Title : Data Scientist – NLP & LLM

Experience Required : 4 to 5+ Years

Location : Gurugram

Notice Period : Immediate Joiner Preferred

Employment Type : Full-Time

Job Summary :

We are seeking a highly skilled Data Scientist with strong expertise in Natural Language Processing (NLP) and modern deep learning techniques. The ideal candidate will have hands-on experience working with NER, RNN, LSTM, Transformers, GPT models, and Large Language Models (LLMs), including frameworks such as spaCy.

Mandatory Skills : NLP, spaCy, NER (Named-entity Recognition), RNN (Recurrent Neural Network), LSTM (Long Short-Term Memory), Transformers, GPT, LLMs, Python

Key Responsibilities :

Design and implement NLP models for tasks like text classification, entity recognition, summarization, and question answering.
Develop and optimize models using deep learning architectures such as RNN, LSTM, and Transformer-based models.
Fine-tune or build models using pre-trained LLMs such as GPT, BERT, etc.
Work with tools and libraries including spaCy, Hugging Face Transformers, and other relevant frameworks.
Perform data preprocessing, feature extraction, and training pipeline development.
Evaluate model performance and iterate with scalable solutions.
Collaborate with engineering and product teams to integrate models into production.

Required Skills :

4 to 5+ years of hands-on experience in Data Science and NLP.
Strong understanding of NER, RNN, LSTM, Transformers, GPT, and LLM architectures.
Experience with spaCy, TensorFlow, PyTorch, and Hugging Face Transformers.
Proficient in Python and its ML ecosystem (NumPy, pandas, scikit-learn, etc.).
Familiarity with prompt engineering and fine-tuning LLMs is a plus.
Excellent problem-solving and communication skills.

Job Title : Data Scientist – NLP & LLM

Experience Required : 4 to 5+ Years

Location : Gurugram

Notice Period : Immediate Joiner Preferred

Employment Type : Full-Time

Job Summary :

Mandatory Skills : NLP, spaCy, NER (Named-entity Recognition), RNN (Recurrent Neural Network), LSTM (Long Short-Term Memory), Transformers, GPT, LLMs, Python

Key Responsibilities :

Design and implement NLP models for tasks like text classification, entity recognition, summarization, and question answering.
Develop and optimize models using deep learning architectures such as RNN, LSTM, and Transformer-based models.
Fine-tune or build models using pre-trained LLMs such as GPT, BERT, etc.
Work with tools and libraries including spaCy, Hugging Face Transformers, and other relevant frameworks.
Perform data preprocessing, feature extraction, and training pipeline development.
Evaluate model performance and iterate with scalable solutions.
Collaborate with engineering and product teams to integrate models into production.

Required Skills :

4 to 5+ years of hands-on experience in Data Science and NLP.
Strong understanding of NER, RNN, LSTM, Transformers, GPT, and LLM architectures.
Experience with spaCy, TensorFlow, PyTorch, and Hugging Face Transformers.
Proficient in Python and its ML ecosystem (NumPy, pandas, scikit-learn, etc.).
Familiarity with prompt engineering and fine-tuning LLMs is a plus.
Excellent problem-solving and communication skills.

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About NeoGenCode Technologies Pvt Ltd

Founded :

2023

Type :

Services

Size

Stage :

Raised funding

About

Welcome to Neogencode Technologies, an IT services and consulting firm that provides innovative solutions to help businesses achieve their goals. Our team of experienced professionals is committed to providing tailored services to meet the specific needs of each client. Our comprehensive range of services includes software development, web design and development, mobile app development, cloud computing, cybersecurity, digital marketing, and skilled resource acquisition. We specialize in helping our clients find the right skilled resources to meet their unique business needs. At Neogencode Technologies, we prioritize communication and collaboration with our clients, striving to understand their unique challenges and provide customized solutions that exceed their expectations. We value long-term partnerships with our clients and are committed to delivering exceptional service at every stage of the engagement. Whether you are a small business looking to improve your processes or a large enterprise seeking to stay ahead of the competition, Neogencode Technologies has the expertise and experience to help you succeed. Contact us today to learn more about how we can support your business growth and provide skilled resources to meet your business needs.

Candid answers by the company

What does the company do?

What is the location preference of jobs?

IT & Engineering Talent Staffing

Provides full-time and contract-based hiring, delivering handpicked, pre‑screened developers across tech stacks—ranging from web, mobile, AI/ML, Web3/blockchain.
Maintains a bench o vetted candidates, offering fast delivery of interview-ready profiles—often within 24 hours.
Offers payroll management, handling compliance, tax, attendance, and documentation for both contractors and full-time employees.

2. End-to-End Project Delivery

Delivers full-stack development solutions: web, mobile, cloud, AI/ML, Blockchain/Web3.
Manages entire project lifecycle—requirements gathering, design (UI/UX), development, deployment, and ongoing support .

3. Additional Offerings

Expands into cybersecurity consulting, digital marketing, and cloud platform services (like AWS, GCP, Azure) .
Provides strategic IT consulting to align technology solutions with business objectives

Company social profiles

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Ideal Candidate

1.Strong Data Scientist / AI Engineer / Generative AI Engineer profile.

2.Mandatory (Experience 1) - Must have 3+ years of hands-on experience in Data Science, Artificial Intelligence, Machine Learning, Deep Learning, NLP, or Generative AI application development.

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4.Mandatory (Experience 3) - Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, or Scikit-learn.

5.Mandatory (Experience 4) - Must have hands-on experience in NLP use cases such as text classification, sentiment analysis, entity recognition (NER), semantic search, embeddings, or document understanding.

6.Mandatory (Experience 5) - Must have experience working with Large Language Models (LLMs) such as GPT, LLaMA, Mistral, Phi, Claude, Gemini, or similar models

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8.Mandatory (Experience 7) - Must have experience with Prompt Engineering and Generative AI frameworks such as LangChain, LangGraph, AI Agents, Azure OpenAI, or similar technologies.

9.Mandatory (Experience 8) - Must have experience developing, consuming, or integrating APIs using Python frameworks such as FastAPI, Flask, or similar technologies.

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17.Mandatory ( Pedigree) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered.

Roles & Responsibilities

Design and develop intelligent AI-based applications using advanced NLP and LLM techniques to solve real-world business challenges in financial services.
Build and optimize Retrieval-Augmented Generation (RAG) pipelines leveraging structured and unstructured financial data.
Integrate and orchestrate LLMs/SLMs for question-answering, summarization, semantic search, and document understanding.
Develop and maintain RESTful APIs (sync and async) to serve NLP models and chatbot interfaces using frameworks like FastAPI, Flask, etc.
Should have knowledge of advanced prompting techniques.
Implement semantic search, hybrid search, and text retrieval systems using Elasticsearch and vector databases (e.g., FAISS, Pinecone, Weaviate).
Perform NLP tasks such as entity recognition, text classification, intent detection, embedding generation, and sentiment analysis where required.
Monitor and fine-tune LLM/SLM performance with real-world user data to improve relevance, latency, and accuracy.
Exposure to LLMOps tools for monitoring, evaluation, and versioning of AI models in production.
Build, train, and evaluate deep learning models for NLP tasks including classification, NER, summarization, and embedding generation.
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