Gen AI / ML Engineers _Virtual Drive_13th August

Role & responsibilities

• Python & Async Frameworks: Strong proficiency in Python 3.x and async web frameworks like FastAPI or Celery to build high-throughput, multi-tenant background processing microservices.
• GenAI & LLM Orchestration: Hands-on experience with LLM APIs (Google Gemini/Vertex AI or OpenAI) and utilizing tools like Pydantic to enforce strict structured JSON outputs from unstructured data.
• Dynamic Prompt Engineering: Expertise in designing complex system instructions, few-shot prompting templates, and managing advanced model parameters like thinking budgets or temperature.
• Cloud Storage & Data Pipelines: Proficient in managing cloud data streams (Google Cloud Storage or S3) to ingest document assets (PDFs/Images) and orchestrating async polling workflows with automated retry logic.
• ML Ingestion & Evaluation: Experience with ML preprocessing tools (Pandas, NumPy, OCR engines) and setting up statistical thresholds to evaluate extraction confidence scores and failure metrics.