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Lead Gen AI Data Scientist - GenAI
Lead Gen AI Data Scientist - GenAIConfidential • Bengaluru / Bangalore
Lead Gen AI Data Scientist - GenAI

Lead Gen AI Data Scientist - GenAI

Confidential • Bengaluru / Bangalore
30+ days ago
Job description
  • Job Description
  • Design and implement advanced solutions utilizing Large Language Models (LLMs).
  • Demonstrate self-driven initiative by taking ownership and creating end-to-end solutions.
  • Conduct research and stay informed about the latest developments in generative AI and LLMs.
  • Develop and maintain code libraries, tools, and frameworks to support generative AI development.
  • Participate in code reviews and contribute to maintaining high code quality standards.
  • Engage in the entire software development lifecycle, from design and testing to deployment and maintenance.
  • Collaborate closely with cross-functional teams to align messaging, contribute to roadmaps, and integrate software into different repositories for core system compatibility.
  • Possess strong analytical and problem-solving skills.
  • Demonstrate excellent communication skills and ability to work effectively in a team environment.
  • Primary Skills
  • Natural Language Processing (NLP) :
  • Hands-on experience in use case classification, topic modeling, Q&A and chatbots, search, Document AI, summarization, and content generation.
  • Computer Vision and Audio :
  • Hands-on experience in image classification, object detection, segmentation, image generation, audio, and video analysis.
  • Generative AI :
  • Proficiency with SaaS LLMs including Langchain, Llama Index, vector databases, prompt engineering (COT, TOT, ReAct, agents).
  • Experience with Azure OpenAI, Google Vertex AI, AWS Bedrock for text / audio / image / video modalities.
  • Familiarity with open-source LLMs and tools like TensorFlow / PyTorch and Hugging Face.
  • Techniques such as quantization, LLM fine-tuning using PEFT, RLHF, data annotation workflow, and GPU utilization.
  • Cloud :
  • Hands-on experience with cloud platforms such as Azure, AWS, and GCP.
  • Cloud certification is preferred.
  • Application Development :
  • Proficiency in Python, Docker, FastAPI / Django / Flask, and Git.
  • Tech Skills (10+ Years Experience)
  • Machine Learning (ML) & Deep Learning :
  • Solid understanding of supervised and unsupervised learning.
  • Proficiency with deep learning architectures like Transformers, LSTMs, RNNs, etc.
  • Generative AI :
  • Hands-on experience with models such as OpenAI GPT-4, Anthropic Claude, LLama, etc.
  • Knowledge of fine-tuning and optimizing large language models (LLMs) for specific tasks.
  • Natural Language Processing (NLP) :
  • Expertise in text preprocessing, tokenization, embeddings, sentiment analysis.
  • Familiarity with NLP tasks like text classification, summarization, translation, and question-answering.
  • Retrieval-Augmented Generation (RAG) :
  • In-depth understanding of RAG pipelines and knowledge retrieval techniques like dense / sparse retrieval.
  • Experience integrating generative models with external knowledge bases or databases to augment responses.
  • Data Engineering :
  • Ability to build, manage, and optimize data pipelines for feeding large-scale data into AI models.
  • Search and Retrieval Systems :
  • Experience building or integrating search and retrieval systems using Elasticsearch, AI Search, ChromaDB, PGVector, etc.
  • Prompt Engineering :
  • Expertise in crafting, fine-tuning, and optimizing prompts to improve model output quality.
  • Knowledge of prompt formats, strategies, constraints, including few-shot, zero-shot, one-shot prompting, and using system / user prompts.
  • Programming & Libraries :
  • Proficiency in Python and libraries such as PyTorch, Hugging Face.
  • Knowledge of version control (Git), cloud platforms (AWS, GCP, Azure), and MLOps tools.
  • Database Management :
  • Experience with SQL, NoSQL, and vector databases.
  • APIs & Integration :
  • Ability to work with RESTful APIs and integrate generative models into applications. Evaluation & Benchmarking :
  • Strong understanding of metrics and evaluation techniques for generative models.
  • Skills Required

    Tensorflow, Pytorch, React

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