AI System Developer

2 days ago

Delhi, Delhi, India beBeeArtificial Full time ₹ 25,00,000 - ₹ 35,00,000
AI Engineering Expert

We are seeking an expert AI engineer with a strong background in Python and Generative AI. This is an exciting opportunity to work on cutting-edge projects that leverage the latest advancements in machine learning and natural language processing.

Responsibilities
  • AI Model Development & Engineering:
    • Develop, train, and deploy complex Generative AI models using architectures like Transformers, GANs, and VAEs.
    • Implement Large Language Models (LLMs) using techniques such as Retrieval-Augmented Generation (RAG) and prompt engineering.
  • Design & Architecture:
    • Design and implement scalable AI applications using Python and modern frameworks, ensuring seamless integration with existing systems.
    • Architect production-grade AI solutions that incorporate event-driven architectures and microservices.
  • & Deployment:
    • Automate the machine learning lifecycle using MLOps principles, from development to deployment.
    • Build and manage continuous integration and deployment pipelines for AI models and applications.
  • & Innovation:
    • Stay current with the latest advancements in Generative AI, machine learning, and NLP, applying this knowledge to drive business value.
    • Conduct research and experimentation to evaluate new models, frameworks, and techniques for potential business impact.
  • & Leadership:
    • Collaborate with cross-functional teams to deliver end-to-end AI solutions that meet business objectives.
    • Provide technical leadership and mentorship to junior team members, fostering growth and development within the team.
Requirements
  • Core Engineering:
    • Expert-level proficiency in Python programming language.
    • Strong software engineering background, including object-oriented programming, data structures, and algorithms.
  • Ai & LLMs:
    • 7-11 years of experience in AI/ML engineering, with a focus on Generative AI and LLMs.
    • Hands-on experience with fine-tuning and RAG techniques.
    • Deep understanding of deep learning frameworks such as PyTorch or TensorFlow.
  • Cloud Platforms:
    • Experience with cloud platforms for AI/ML, including AWS, Azure, or GCP.
    • Hands-on experience with MLOps tools and containerization technologies.
  • APIs:
    • Experience with vector databases and SQL.
    • Proficiency in building and consuming RESTful APIs.

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