about 11 hours ago
Responsibilities
- Contribute to the architecture and ownership of AI system design and deployment.
- Develop end-to-end Generative AI features including backend services and model integration.
- Integrate and optimize LLMs for business planning use cases.
- Build conversational interfaces and workflows for natural language interaction.
- Implement evaluation frameworks to measure GenAI feature quality.
- Design APIs to expose AI capabilities for integrations.
- Optimize model inference pipelines for performance and scalability.
- Implement monitoring and observability for GenAI systems.
- Participate in code reviews and mentor junior engineers.
Requirements
- Extensive hands-on experience in Artificial Intelligence and Machine Learning.
- End-to-end exposure in model lifecycle development and deployment.
- Strong knowledge of LLM APIs and conversational AI patterns.
- Experience fine-tuning LLMs for enterprise applications.
- Familiarity with MLOps and LLMOps for scalable model deployments.
- Proficiency in Python and modern software development practices.
Tech Stack
MLflowPython