AIML Engineer FB
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Job Location:
Monthly Salary:
Posted on:
3 hours ago
Vacancies:
1 Vacancy
Job Summary
Job Description:
build a suite of AI-driven Accelerators and Autonomous Agents designed to automate the entire lifecycle of our Data Platform-from legacy migration and pipeline construction to incident response and ML lifecycle management.
Your goal is to turn the Data Platform into a self-service self-healing ecosystem. Agent Orchestration: Expertise in LangChain CrewAI or AutoGPT to build multi-agent workflows.
Code Generation: Proven experience using LLMs for Code-to-Code translation (specifically SQL to dbt/Python).
RAG Mastery: Building advanced Retrieval-Augmented Generation systems over technical documentation data catalogs and codebases.
Expert dbt: Deep knowledge of dbt Jinja Macros and Mesh-essential for teaching an AI how to write good code.
Spark & Lakehouse: Understanding of Spark internals to build agents that can optimize job performance and resolve OOM (Out of Memory) errors.
Cloud Infrastructure: Experience with GCP (Vertex AI) or equivalent cloud AI suites.
Agent Orchestration: Expertise in LangChain CrewAI or AutoGPT to build multi-agent workflows.
Code Generation: Proven experience using LLMs for Code-to-Code translation (specifically SQL to dbt/Python).
RAG Mastery: Building advanced Retrieval-Augmented Generation systems over technical documentation data catalogs and codebases. Expert dbt: Deep knowledge of db
build a suite of AI-driven Accelerators and Autonomous Agents designed to automate the entire lifecycle of our Data Platform-from legacy migration and pipeline construction to incident response and ML lifecycle management.
Your goal is to turn the Data Platform into a self-service self-healing ecosystem. Agent Orchestration: Expertise in LangChain CrewAI or AutoGPT to build multi-agent workflows.
Code Generation: Proven experience using LLMs for Code-to-Code translation (specifically SQL to dbt/Python).
RAG Mastery: Building advanced Retrieval-Augmented Generation systems over technical documentation data catalogs and codebases.
Expert dbt: Deep knowledge of dbt Jinja Macros and Mesh-essential for teaching an AI how to write good code.
Spark & Lakehouse: Understanding of Spark internals to build agents that can optimize job performance and resolve OOM (Out of Memory) errors.
Cloud Infrastructure: Experience with GCP (Vertex AI) or equivalent cloud AI suites.
Agent Orchestration: Expertise in LangChain CrewAI or AutoGPT to build multi-agent workflows.
Code Generation: Proven experience using LLMs for Code-to-Code translation (specifically SQL to dbt/Python).
RAG Mastery: Building advanced Retrieval-Augmented Generation systems over technical documentation data catalogs and codebases. Expert dbt: Deep knowledge of db
