Job Summary
Key Responsibilities
2. Troubleshoot and resolve bugs in LLM-based modules by utilizing RESTful APIs and database queries with PostgreSQL and VectorDB.
3. Implement and test prompt engineering strategies to optimize LLM outputs, supporting new feature development and minor enhancements.
4. Develop and integrate RESTful APIs using frameworks such as Flask, Django, or FastAPI to enable seamless communication between GenAI components.
5. Support data storage and retrieval tasks by writing queries and managing schemas in PostgreSQL and VectorDB, ensuring data integrity for GenAI models.
6. Participate in code reviews and documentation activities, contributing to CMMi and client requirement documents for GenAI solutions.
Skill Requirements
2. Good Proficiency In Python Programming For Genai Development.
3. Experience With Restful Api Creation And Integration Using Flask, Django, Or Fastapi.
4. Familiarity With Database Management Using Postgresql, Mysql, And Vectordb Technologies Such As Pinecone.
5. Basic Knowledge Of Embedding Techniques And Azure Ai Search For Genai Solutions.
6. Ability To Participate In Code Reviews And Technical Documentation Processes.
Other Requirements
2. Google Cloud Professional Machine Learning Engineer