
AI and GenAI Visionary
2 weeks ago
Leading the Evolution of AI and GenAI
- Key Responsibilities:
- Advance problem discovery, root cause analysis, and action recommendation by collaborating with data scientists, GenAI developers, and ML engineers to develop and deploy advanced LLM, SLM, and RAG-based models for real-time and batch processing scenarios.
- Gen-AI-Powered Insights Generation: Lead data scientists in creating and fine-tuning Generative AI models to translate complex data patterns and root cause findings into actionable insights for business stakeholders.
- Reference Architectures and Platform Optimization: Work with technical architects to evolve frameworks for augmenting and evolving batch processing data architectures with streaming architectures.
- Client Deployments and MLOps Practices: Provide guidance on creating automated data pipelines for raw data and engineered features. Establish robust MLOps practices, including automated model monitoring, retraining triggers, and performance benchmarking.
- Use Case Development and Platform Demonstration: Lead development of use cases on the platform for various vertical problem statements.
- Key Qualifications:
- Mentor a team of data scientists and machine learning engineers, providing guidance on best practices in GenAI, AI/ML methodologies, and coding standards.
- Collaborate with product managers, data engineers, and business analysts to align AI solutions with platform goals and user requirements.
Required Skills:
- GenAI, AI/ML methodologies
- Leadership and collaboration
- Data engineering and architecture
- Machine learning engineering
Achieve Success in this Role:
- Develop and implement innovative AI solutions that drive business growth and improvement.
- Lead cross-functional teams to design and deploy scalable, high-performing AI models.
- Foster a culture of innovation, experimentation, and continuous learning.
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