Engineer - Gen AI

1 day ago

Gurugram, India Intersoft Data Labs Full time

We are seeking an experienced Generative AI professional with expertise in designing and deploying Large Language Models (LLMs) from scratch as well as fine-tuning and optimizing existing models. The role requires deep technical skills, creativity, and hands-on experience in building scalable GenAI solutions across text, image, and multimodal domains.

Key Responsibilities:

  • Design and build LLMs from scratch, including data pipeline creation, tokenization strategies, and training at scale.
  • Fine-tune and optimize pre-trained models for specific enterprise use cases.
  • Research, experiment with, and implement cutting-edge architectures in generative AI (transformers, diffusion, multimodal).
  • Develop prompt engineering, RAG (Retrieval Augmented Generation), and knowledge integration pipelines.
  • Collaborate with cross-functional teams to translate business problems into GenAI-powered solutions.
  • Deploy and monitor models in production with focus on scalability, security, and performance.
  • Ensure compliance with ethical AI practices, governance, and responsible AI usage.
  • Document design, experiments, and best practices to contribute to organizational AI knowledge base.

Required Skills & Qualifications:

  • Proven experience in LLM design and training from scratch, including data preparation, distributed training, and evaluation.
  • Strong background in deep learning, NLP, and transformer architectures.
  • Strong development experience in Python development and ML frameworks.
  • Hands-on experience with vector databases (FAISS, Pinecone, Weaviate, Milvus) and RAG pipelines.
  • Solid understanding of MLOps practices, containerization (Docker, Kubernetes).
  • Must have Good Experience in AWS Cloud and its Services.
  • Ability to optimize model inference, reduce latency, and manage large-scale deployments.
  • Strong problem-solving, analytical, and communication skills.

Preferred Qualifications:

  • Research or published work in LLMs or generative AI.
  • Contributions to open-source AI frameworks or libraries.
  • Exposure to multimodal AI (vision-language models, audio, video).
  • Familiarity with AI regulation, compliance, and governance standards.

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