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Lead Gen AI Data Scientist - GenAI

Lead Gen AI Data Scientist - GenAI

ConfidentialGurgaon / Gurugram, Bengaluru / Bangalore
30+ days ago
Job description

Responsibilities :

  • 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 the ability to work effectively in a team environment.

Primary Skills :

  • Natural Language Processing (NLP) : Hands-on experience in use case classification, topic modeling, QA 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 Lang chain, 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, including tools like TensorFlow / Pytorch and huggingface. Techniques such as quantization, LLM finetuning 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) :

    1.Machine Learning (ML) Deep Learning :

  • Solid understanding of supervised and unsupervised learning.
  • Proficiency with deep learning architectures like Transformers, LSTMs, RNNs, etc.
  • 2. Generative AI :

  • Hands-on experience with models such as OpenAI GPT4, Anthropic Claude, LLama etc.
  • Knowledge of fine-tuning and optimizing large language models (LLMs) for specific tasks.
  • 3. Natural Language Processing (NLP) :

  • Expertise in NLP techniques, including text preprocessing, tokenization, embeddings, and sentiment analysis.
  • Familiarity with NLP tasks such as text classification, summarization, translation, and question-answering.
  • 4. Retrieval-Augmented Generation (RAG) :

  • In-depth understanding of RAG pipelines, including knowledge retrieval techniques like dense / sparse retrieval.
  • Experience integrating generative models with external knowledge bases or databases to augment responses.
  • 5. Data Engineering :

  • Ability to build, manage, and optimize data pipelines for feeding large-scale data into AI models.
  • 6. Search and Retrieval Systems :

  • Experience with building or integrating search and retrieval systems, leveraging knowledge of Elasticsearch, AI Search, ChromaDB, PGVector etc.
  • 7. Prompt Engineering :

  • Expertise in crafting, fine-tuning, and optimizing prompts to improve model output quality and ensure desired results.
  • Understanding how to guide large language models (LLMs) to achieve specific outcomes by using different prompt formats, strategies, and constraints.
  • Knowledge of techniques like few-shot, zero-shot, and one-shot prompting, as well as using system and user prompts for enhanced model performance.
  • 8. Programming Libraries :

  • Proficiency in Python and libraries such as PyTorch, Hugging Face, etc.
  • Knowledge of version control (Git), cloud platforms (AWS, GCP, Azure), and MLOps tools.
  • 9. Database Management :

  • Experience working with SQL and NoSQL databases, as well as vector databases
  • 10. APIs Integration :

  • Ability to work with RESTful APIs and integrate generative models into applications.
  • 11. Evaluation Benchmarking :

  • Strong understanding of metrics and evaluation techniques for generative models.
  • Skills Required

    Nlp, Docker, Azure, Python, Aws

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