
Chief Architect of Large Language Models
7 days ago
Job Title: Director of Artificial Intelligence
Job OverviewWe are seeking a visionary leader to design and oversee the overall architecture for large language models (LLMs), ensuring alignment with business objectives.
Main Responsibilities- Develop a strategic technical roadmap in line with organizational goals, defining key initiatives and priorities.
- Select the technology stack, frameworks, and tools for LLM development and deployment, ensuring scalability and modularity.
- Oversee the integration of data pipelines, model training environments, and deployment infrastructure, guaranteeing seamless collaboration between teams.
- Identify potential technical risks and develop mitigation strategies, minimizing downtime and ensuring high availability.
- Collaborate with data scientists, engineers, domain experts, and stakeholders to drive cohesive implementation and foster a culture of innovation.
- Stay up-to-date with AI advancements and incorporate best practices to improve LLM capabilities, continually pushing the boundaries of what is possible.
- Conduct in-depth research on LLM architectures, including open-source and domain-specific models like GPT, BERT, and FinBERT, identifying opportunities for optimization and improvement.
- Demonstrated expertise in AI, ML, NLP, and large language models (LLMs), with a strong understanding of their applications and limitations.
- A deep grasp of scalability, modularity, and security principles, ensuring that solutions are robust, reliable, and secure.
- Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud, with a proven track record of successful deployments.
- Familiarity with big data technologies, data pipeline design, and data management practices, ensuring that data is collected, processed, and stored efficiently.
- Expertise in CI/CD, deployment, and monitoring for ML models, ensuring that solutions are scalable, reliable, and maintainable.
- Ability to guide technical teams and communicate effectively with stakeholders, both technical and non-technical.
- Strong analytical skills for addressing complex technical challenges, with a logical and methodical approach to problem-solving.
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