Intern AI/ML/Data Engineer

Responsibilities

‍• Modern Data Stack: Collaborate with the engineering team to migrate systems from PostgreSQL/GraphQL to the Google Cloud Platform ecosystem (BigQuery, Cloud Storage).

• AI Agent Development: Actively participate in building and optimizing AI Chatbots/Agents using RAG (Retrieval-Augmented Generation) techniques to solve data analysis and automated reporting problems.

• LLM Integration: Integrate and fine-tune models such as Gemini, GPT-4, and Claude using frameworks like LangChain or LlamaIndex.

• Data Pipeline: Design and operate high-performance ETL/ELT pipelines, ensuring clean and reliable data flow for AI models and dashboards.• Visualization: Build interactive dashboards using Looker or Power BI to present AI-driven insights.

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Requirements

‍• Technical Background: Currently pursuing or holding a degree in IT, Data Science, Computer Science, or related fields.

• SQL Mastery: Strong ability to write complex SQL queries (Joins, Window Functions, CTEs) and solid understanding of data structures.

• AI/ML Mindset: Understanding of how LLMs work, prompt engineering, and embedding mechanisms (Embeddings/Vector Databases).

• Programming Language: Proficient in Python (experience with Pandas, PyTorch, or TensorFlow is a plus).

• Product Mindset: Ability to self-research and apply new technologies such as Vertex AI and MLOps in real-world scenarios.

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Nice to Have

‍• Experience working on personal projects involving Chatbots, RAG systems, or using APIs from OpenAI/Google AI.

• Familiarity with Docker or knowledge of Cloud platforms (GCP/AWS/Azure).‍

Benefits

‍• Cutting-edge Technology Exposure: Work directly with Vertex AI and some of the most advanced LLMs available today.

• Career Growth: Structured training roadmap to become a professional AI Engineer or Analytics Engineer.

• Work Environment: Young, dynamic culture that encourages experimentation (fail fast, learn fast).

• Compensation: Competitive internship allowance/salary.