Data Scientist - LLM Models

Key Responsibilities :

Machine Learning (ML) :

- Design, build, and deploy ML pipelines for structured and unstructured data.

- Conduct feature engineering, model selection, and hyperparameter tuning.

- Evaluate model performance using industry-standard metrics and improve accuracy.

- Collaborate with data engineering teams to ensure clean and accessible data for model training.

- Apply supervised, unsupervised, and reinforcement learning techniques as per use case.

Natural Language Processing (NLP) :

- Develop NLP pipelines for text classification, sentiment analysis, entity recognition, summarization, etc.

- Leverage libraries like spaCy, NLTK, Hugging Face Transformers, and Gensim.

- Preprocess and tokenize large corpora using advanced NLP methods.

- Implement solutions for multi-lingual, domain-specific text data challenges.

- Integrate NLP services with applications or workflows.

Large Language Models (LLM) :

- Fine-tune and deploy LLMs (e.g., GPT, LLaMA, BERT, Falcon, Mistral) on custom datasets.

- Use prompt engineering and retrieval augmented generation (RAG) to build intelligent systems.

- Optimize inference performance and latency for production-level deployment.

- Stay updated with the latest in GenAI, foundation models, and transformer architectures.

- Work on use cases like chatbots, question answering, summarization, content generation, and

semantic search.

Role : Manager - Data Science

Industry Type : IT Services & Consulting

Department : Data Science & Analytics

Employment Type : Full Time, Permanent

Role Category : Data Science & Machine Learning

Education

UG: Any Graduate