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Brainwonders

AI Engineer Intern

Posted 8 Days Ago
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In-Office
Mumbai, Maharashtra
Internship
In-Office
Mumbai, Maharashtra
Internship
The AI Engineer Intern will work on building and testing LLM applications, deploying models on AWS, and experimenting with AI frameworks and transformers.
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Company Description

BRAINWONDERS

About Company:
At Brainwonders, we are proud to be India’s largest career counselling and guidance company, recognized for our commitment to transforming students' futures. With 1223+ educational institutes using our services, 93+ corporate connections, and 108+ franchisees, we have built an expansive network of support for students, educators, and professionals.

Brainwonders has earned numerous national and regional awards for excellence in career counselling and guidance, and is consistently rated as one of the highest-paying employers in the counselling industry by various job portals.

Job Description

AI Engineer Intern – LLMs, Agents, AWS
Position: AI Engineer Intern
Experience: 0-1 Year (Final-year students or freshers welcome)
Location: Borivali East, Mumbai 
Type: Internship (3–6 months) | Possibility of Full-time Offer

🧠 Focus Areas:
Large Language Models (LLMs)

AI Agents / Autonomous Systems

ML Fundamentals & Transformers

Cloud Deployment & Scaling (AWS)

🎯 Responsibilities:
Build and test LLM-based applications and workflows.

Experiment with agent frameworks (e.g., LangGraph, CrewAI).

Use and adapt transformer models (e.g., LLaMA, Mistral) for domain tasks.

Deploy models and services on AWS (Lambda, EC2, SageMaker).

Work with vector stores and embeddings for search or RAG-based systems.

Collaborate on prompt engineering, fine-tuning, and pipeline optimization.

✅ Requirements:
Solid understanding of LLMs, tokenization, transformers.

Python programming (Pandas, NumPy, Hugging Face, LangChain, etc.).

Exposure to AWS services like EC2, Lambda, S3, or SageMaker.

Eagerness to explore real-world AI use cases (agents, copilots, RAG).

Basic ML knowledge and hands-on project experience.

💡 Good to know:
Experience with serverless deployments on AWS.

Familiarity with monitoring and logging (e.g., CloudWatch, OpenTelemetry).

Contributions to open-source AI tools or models

Additional Information

 

 

Top Skills

AWS
Ec2
Hugging Face
Lambda
Langchain
Numpy
Pandas
Python
Sagemaker

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