Chief Architect

3 days ago

Solapur, Maharashtra, India beBeeGenai Full time ₹ 2,50,00,000 - ₹ 3,50,00,000
Chief Architect - AI and GenAI Innovator

The organization seeks an accomplished Chief Architect to spearhead the development of cutting-edge AI and GenAI solutions.

  • Main Responsibilities:
  • • Advanced AI and GenAI for Problem Discovery, RCA and Action Recommendation: Oversee a team of data scientists, GenAI developers, and ML engineers. Develop advanced LLM, SLM, and RAG based models along with classical machine learning models including anomaly detection, predictive analytics, causal inferencing, and action recommendation models.
  • • Gen-AI-Powered Analysis and Insights Generation: Lead data scientists in creating and fine-tuning Generative AI models to assist in analysis creation for problem discovery, translating complex data patterns and root cause findings into actionable insights for stakeholders.
  • • Reference Architectures: Collaborate with Technical Architects to evolve frameworks for augmenting and evolving batch processing data architectures with streaming architectures to support connected data and ML pipeline executions in real-time.
  • • Client Deployments of the Platform: Provide guidance on creating automated data pipelines for raw data and engineered features ensuring data quality, integrity, and accessibility for model training and inference.
  • • Development of Use Cases: Lead and support development of use cases on the platform for various vertical specific problem statements.
  • • Leadership and Collaboration: Lead and mentor a team of data scientists and machine learning engineers, providing guidance on best practices in GenAI, AI/ML methodologies, and coding standards.

Requirements:

  • In-depth understanding of Statistics, Classical Machine Learning, Deep Learning, and GenAI along with significant hands-on experience in these areas.
  • Able to understand business problems in various domains, quickly grasp problem discovery analysis and modelling imperatives, and translate those into requirements for AI models.
  • Significant exposure to proprietary & open-source cloud-based Machine Learning platforms.
  • Experience in leveraging open-source LLMs and prompt engineering, RAG based training, and SLM model development.
  • Hands-on with excellent ML programming skills in Python using open-source libraries.
  • Experience working with RDBMS and NoSQL databases; Exposure to Big Data technologies.

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