
Data Scientist
2 weeks ago
About the Role
We are seeking a highly skilled Data Scientist with expertise in Large Language Models (LLMs) to join our AI/ML team. The ideal candidate will have strong foundations in NLP, deep learning, and applied machine learning with practical experience in building, fine-tuning, and deploying LLM-based solutions.
Key Responsibilities
- Design, train, and fine-tune Large Language Models (LLMs) for real-world applications.
- Apply techniques such as prompt engineering, few-shot learning, and transfer learning.
- Work with embeddings, vector databases, and retrieval-augmented generation (RAG).
- Analyze large datasets to build, evaluate, and optimize NLP pipelines.
- Implement model performance monitoring, evaluation metrics, and continuous improvements.
- Collaborate with cross-functional teams to integrate LLM-based solutions into products.
- Stay updated with the latest research in NLP, LLMs, and generative AI.
Requirements
- Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or related field.
- 2+ years of hands-on experience in NLP or Deep Learning.
- Strong experience with Python, PyTorch/TensorFlow, Hugging Face Transformers.
- Experience with LLM fine-tuning (LoRA, PEFT, full fine-tuning).
- Knowledge of vector databases (e.g., Pinecone, Weaviate, FAISS).
- Experience with prompt engineering and evaluation frameworks.
- Strong understanding of ML evaluation metrics (perplexity, BLEU, ROUGE, etc.).
- Familiarity with deploying ML/LLM models in production environments.
Nice to Have
- Experience with cloud platforms (AWS, GCP, Azure).
- Knowledge of MLOps and CI/CD pipelines for ML models.
- Contributions to open-source NLP/LLM projects.
What We Offer
- Competitive salary and benefits package.
- Opportunity to work on cutting-edge Generative AI projects.
- Collaborative and innovative work culture.
Job Type: Full-time
Application Question(s):
- Do you have experience with fine-tuning LLMs (e.g., GPT, LLaMA, Falcon)? (Yes/No)
- Which libraries have you used for NLP/LLMs? (One word: e.g., Transformers, LangChain, etc.)
- Have you implemented prompt engineering techniques in real projects? (Yes/No)
- Do you have hands-on experience with vector databases like Pinecone, FAISS, or Weaviate? (Yes/No)
- One word: Which framework do you prefer — PyTorch or TensorFlow?
- Have you worked on Retrieval-Augmented Generation (RAG) pipelines? (Yes/No)
- Do you have experience with LoRA/PEFT fine-tuning? (Yes/No)
- Have you deployed an LLM model in a production environment? (Yes/No)
- What's your experience level with Hugging Face Transformers? (Beginner/Intermediate/Advanced)
- Are you open to working on both research and production-level applications of LLMs? (Yes/No)
Work Location: In person
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