Designation: NLP Engineer (Natural Language Processing Engineer)
Job Location: Permanent Work from Home (Office location is Bangalore, but Permanent Work from home is being provided to all the employees. Candidates anywhere from India can apply.)
Experience: 4 to 6 years
Notice period: Immediate joiner or a maximum of 30 days
We are looking for a skilled and motivated NLP (Natural Language Processing) Engineer with 4 to 6 years of experience in developing and deploying NLP models and applications. The ideal candidate should have a strong foundation in machine learning, a deep understanding of language processing, and hands-on experience in building NLP solutions.
Key Responsibilities:
Model Development:
- Design, implement, and optimize NLP models, including tokenization, named entity recognition (NER), sentiment analysis, text classification, and more.
- Utilize state-of-the-art machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Hugging Face) to build robust NLP models.
Text Processing & Analysis:
- Develop and refine techniques for processing large volumes of unstructured text data.
- Implement algorithms for text normalization, stemming, lemmatization, and parsing.
Data Preprocessing:
- Clean, preprocess, and annotate text data to ensure it is suitable for model training and evaluation.
- Work with domain experts to ensure the accuracy and relevance of training datasets.
Algorithm Implementation:
- Implement and fine-tune algorithms for various NLP tasks, such as text summarization, machine translation, and information retrieval.
- Continuously improve the performance of NLP models through iterative testing and optimization.
Deployment & Integration:
- Deploy NLP models into production environments, ensuring scalability, reliability, and performance.
- Collaborate with software engineers to integrate NLP solutions into larger applications or systems.
Research & Innovation:
- Stay updated on the latest advancements in NLP and related fields.
- Experiment with new techniques and technologies to enhance existing NLP capabilities and explore new applications.
Desired Skills:
Technical Proficiency:
- Strong programming skills in Python, with experience in libraries like NLTK, SpaCy, and scikit learn.
- Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch) and NLP-specific tools (e.g., Hugging Face Transformers).
Machine Learning:
- Solid understanding of machine learning concepts and techniques, particularly in the context of NLP.
- Experience with supervised and unsupervised learning, as well as transfer learning techniques.
NLP Techniques:
- Hands-on experience with NLP techniques, including but not limited to part-of-speech tagging, dependency parsing, word embeddings (e.g., Word2Vec, GloVe), and transformer models (e.g., BERT, GPT).
Problem-Solving & Analytical Skills:
- Strong analytical skills to diagnose issues and improve NLP model performance.
- Ability to troubleshoot and resolve issues related to model accuracy, bias, and efficiency.
Additional Qualifications (Good to Have):
- Knowledge of Big Data Technologies.
- Experience working with large-scale data processing frameworks like Hadoop or Spark.
Experience with Cloud Platforms:
- Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) and their NLP-related services.
Communication & Collaboration:
- Excellent communication skills, with the ability to explain complex technical concepts to non technical stakeholders. Ability to work effectively in a team environment, collaborating with data scientists, engineers, and product managers.
