NLP Engineer

  • Full Time
  • India

CareerNinja | LearnTube

About Us:

LearnTube is a global, AI-driven product that transforms the scattered content of the internet and YouTube into bite-sized courses complete with a structured path, auto-generated assessments & peer-interactions. Hyper-personalised course content is further generated specific to each user & their goal. We have 6 Lakh Learners, across 64 different countries & 2112 cities in India. LearnTube provides 200+ Skill courses in domains like Tech, Marketing, Data Science and Design. These courses are rated an awesome 4.8/5 & are delivered through an easy-to-use Whatsapp Bot, a mobile and a web app. Our courses are co-certified by global brands liks Canva, Zoho, Hootsuite, Semrush, Wix & more while 900+ companies including brands like Amazon, Schbang, Foxymoron, Publicis media, Popxo, DU Times hire from us.

Latest Press Coverage:

Wellfound (formerly Angelist) featured LearnTube in it’s Top 10 Global Ed-Tech Startups due to its innovative work done by a top team! Check out the article here! The founder of LearnTube, Mr Shronit Ladhani has a single vision: to build a billion courses for a billion people. Courses are hyper-personalised, affordable, engaging & leading to outcomes. Check out his LinkedIn here

Your Role:

As we are an AI-powered Edtech company, your main goal would be utilizing Artificial Intelligence for Education. You will be working on building a personalized course creation system, video processing and recommendation engine, knowledge graphs & other such projects end to end from development to deployments.

Responsibilities:

  • Prototype ideas rapidly, drive architecture discussions, and propose solutions to system and product changes.
  • Prompt engineering LLMs like GPTs, LLaMA, Claude for various NLP tasks for zero-shot/few-shot inference.
  • Build recommendation engines that personalize content for the learners.
  • Select/collect appropriate annotated data for training/fine-tuning ML models.
  • Use effective text representations to transform natural language into useful features.
  • Develop & train ML/DL/NLP models according to requirements.
  • Extend ML libraries and frameworks to apply in NLP tasks.
  • Test and deploy trained models/systems on cloud services i.e.
  • AWS/GCP/Azure.

Requirements:

  • Bachelor’s degree or higher in Computer Science or related field.
  • Minimum of 2 years of experience in NLP, Machine Learning, and Deep Learning. Knowledge of Deep Learning model optimization, transfer learning, and prompt engineering with LLMs like GPT3, GPT3.5, GPT4, and Claude.
  • Experience with state-of-the-art NLP models such as GPT, BERT, T5, and transformer-based models.
  • Familiarity with NLP techniques, libraries, and technologies, including Spacy, NLTK, Gensim, and Hugging Face transformers.
  • Proven ability to develop, deploy, and monitor large scale systems in production environments.
  • Knowledge on MLOps – FastAPI/Flask, Docker and/or Kubernetes, CI/CD, and Git is desirable.
  • Familiarity with cloud environments like AWS or GCP or Azure.
  • Knowledge on SQL and NoSQL database experience is preferred.
  • Experience in building Knowledge graphs using Neo4j is preferred. Expertise in Python, and ML libraries like Numpy, Scikit-learn, and Pandas.
  • Proficiency in ML frameworks like PyTorch, TensorFlow, and Keras.
  • Ability to work as a team player and independently.
  • Excellent communication, multi-tasking, and time-management skills with the ability to prioritize tasks.

Why Work With Us:

We take growth and learning seriously. Working with us could be your best decision if you’re looking to grow 5x more in the same amount of time. We offer cross functional learning & ownership along with the chance to work on and scale an exciting, fast growing product. You will be given real responsibilities, freedom to make decisions and come up with ideas and work closely with the founder and the core team, all in a flexible, casual and young (mostly under 30) work environment. Flexible work, free drinks and snacks, off-sites etc are just a regular part of our work life.

To apply for this job please visit in.linkedin.com.

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