Chief Intelligence Architect

2 days ago

Mangalore, Karnataka, India beBeeArtificialIntelligence Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

Job Opportunity:

We are seeking a highly skilled AI/ML Architect with expertise in large language models (LLMs) to join our organization.

Key Responsibilities:

  • Develop and oversee the architecture for LLMs, ensuring alignment with business objectives and strategic goals.
  • Create a technical strategy and roadmap that aligns with organizational needs and priorities.
  • Select technology stacks, frameworks, and tools for LLM development and deployment, considering scalability, modularity, and security principles.
  • Oversee the integration of data pipelines, model training environments, and deployment infrastructure, ensuring seamless data flow and efficient model deployment.
  • Identify potential technical risks and define mitigation strategies to ensure successful project outcomes.
  • Collaborate with data scientists, engineers, domain experts, and stakeholders to drive cohesive implementation and achieve shared goals.
  • Stay up-to-date with the latest advancements in AI and incorporate best practices to improve LLM capabilities and drive innovation.
  • Conduct research on LLM architectures, including open-source and domain-specific models like GPT, BERT, and FinBERT, to identify opportunities for improvement and growth.

Required Skills and Qualifications:

  • AI/ML Expertise: Deep knowledge in AI, ML, NLP, and LLMs, with a focus on cutting-edge technologies and methodologies.
  • Software Architecture: Strong grasp of scalability, modularity, and security principles, with experience in designing and implementing scalable software systems.
  • Cloud Proficiency: Hands-on experience with cloud platforms, including AWS, Azure, or Google Cloud, with a focus on deploying and managing large-scale applications.
  • Data Architecture: Knowledge of big data technologies, data pipeline design, and data management practices, with a focus on data quality, integrity, and security.
  • MLOps: Expertise in CI/CD, deployment, and monitoring for ML models, with a focus on automating and streamlining the machine learning lifecycle.
  • Leadership: Ability to guide technical teams and communicate effectively with stakeholders, driving collaboration and achieving shared goals.
  • Problem-Solving: Strong analytical skills for addressing complex technical challenges, with a focus on finding creative solutions and driving innovation.

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