Head of Artificial Intelligence Innovation

1 day ago

Erode, Tamil Nadu, India beBeeArtificialIntelligence Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Lead AI Strategist

We are seeking a visionary leader to spearhead our artificial intelligence initiatives. As Lead AI Strategist, you will oversee the development of large language models (LLMs) and ensure alignment with business objectives.

Key Responsibilities
  • Develop AI Architecture: Design the overall architecture for the LLM, incorporating scalability, modularity, and security principles.
  • Define Technical Strategy & Roadmap: Develop a technical strategy and create a roadmap in line with organizational goals, leveraging expertise in AI, ML, NLP, and cloud technologies.
  • Select Technology Stack: Decide on the technology stack, frameworks, and tools for LLM development and deployment, considering factors such as scalability, security, and cost-effectiveness.
  • Manage Integration: Oversee integration of data pipelines, model training environments, and deployment infrastructure, ensuring seamless collaboration between teams.
  • Risk Management: Identify potential technical risks and define mitigation strategies, staying up-to-date with the latest advancements in AI and ML.
  • Collaborate with Teams: Work closely with data scientists, engineers, domain experts, and stakeholders to drive cohesive implementation and achieve shared goals.
  • Innovate & Improve Practices: Stay at the forefront of AI research and development, incorporating best practices to improve LLM capabilities and drive innovation within the organization.

Required Skills & Qualifications

  • AI/ML Expertise: Deep knowledge in AI, ML, NLP, and large language models (LLMs), including experience with open-source and domain-specific models like GPT, BERT, and FinBERT.
  • Software Architecture: Strong grasp of scalability, modularity, and security principles, with hands-on experience designing and implementing robust software systems.
  • Cloud Proficiency: Hands-on experience with AWS, Azure, or Google Cloud, with a solid understanding of cloud-based architectures and deployments.
  • Data Architecture: Knowledge of big data technologies, data pipeline design, and data management practices, with experience working with large datasets and complex data infrastructures.
  • MLOps: Expertise in CI/CD, deployment, and monitoring for ML models, with a focus on ensuring efficient and scalable model operations.
  • 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 delivering innovative solutions that meet business needs.

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