AI/ML Intern (Generative AI, Agentic AI & Machine Learning)

AI/ML Intern (Generative AI, Agentic AI & Machine Learning)

Company

ESTROC

Website

https://estroc.co.in

Job Type

Internship

Compensation

Starting from ₹10,000 per month

Duration

3–6 Months

Work Mode

Remote (India) | Hybrid coordination in Delhi NCR

Working Hours

Flexible, approximately 30 hours per week

Start Date

Immediate

Experience

Students, Freshers and Candidates with 0–1 Year Experience

About the Internship

ESTROC is looking for curious, technically motivated AI/ML Interns who want to build real-world intelligent applications and contribute to modern AI-powered products.

This internship offers hands-on exposure to Machine Learning, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, Computer Vision and intelligent automation.

You will work on practical engineering assignments, internal products and client-oriented projects, collaborating with the development team to research, build, test, integrate and deploy AI-powered solutions.

We value practical problem-solving, experimentation and the willingness to learn over simply knowing a long list of technologies.

Areas of Work (Priority)

Candidates may express interest in one or more areas

Generative AI & LLM Engineering: LLM applications, prompt engineering, model integration and AI-powered assistants.

Agentic AI & Multi-Agent Systems: AI agents, tool calling, autonomous workflows and intelligent automation.

Machine Learning & Deep Learning: Model development, training, evaluation, experimentation and optimization.

RAG & Knowledge Systems

Document processing, embeddings, vector databases, semantic search and retrieval pipelines.

Computer Vision & NLP

Image processing, OCR, object detection, text analytics and language-based applications.

AI Engineering & MLOps

Model serving, API integration, deployment, monitoring and scalable AI infrastructure.

Key Responsibilities

Develop, test and integrate Machine Learning and AI-powered applications.

Build LLM-based applications, AI assistants, chatbots and intelligent automation workflows.

Experiment with open-source and commercial AI models and APIs.

Develop RAG pipelines using document processing, embeddings, vector databases and semantic retrieval.

Build and experiment with AI agents, LangChain, LangGraph and multi-agent workflows.

Work on data preprocessing, feature engineering, model training and evaluation.

Explore computer vision, OCR, NLP and deep learning applications.

Develop backend services and REST APIs for AI model integration.

Assist in deploying AI solutions using cloud platforms and containerized environments.

Debug, evaluate and optimize model performance, accuracy, latency and reliability.

Maintain clean, reusable and well-documented code using Git and GitHub.

Research emerging AI technologies and implement relevant proof-of-concepts.

Collaborate with frontend, backend and product teams to integrate AI capabilities into complete applications.

Technical Skills & Preferred Technologies

Programming & Data Science

Python

NumPy, Pandas, Matplotlib

Scikit-learn

Data preprocessing and feature engineering

SQL and database fundamentals

Machine Learning & Deep Learning

TensorFlow or PyTorch

Supervised and unsupervised learning

Neural networks and model evaluation

Computer Vision and NLP fundamentals

Generative AI & Agentic Systems

OpenAI, Gemini, Claude, Groq and other LLM APIs

Prompt Engineering

LangChain and LangGraph

Agentic workflows and tool calling

Retrieval-Augmented Generation (RAG)

Embeddings and vector databases such as Pinecone, FAISS, Chroma or Qdrant

Backend, APIs & Cloud

FastAPI or Flask

REST API development and integration

Docker and Git/GitHub

AWS, Microsoft Azure or Google Cloud Platform (GCP)

Model deployment and basic MLOps concepts

Candidates are not expected to know every technology. Strong Python fundamentals, basic ML understanding, curiosity and the ability to build and explain projects are more important.

What You'll Learn

Building real-world AI and ML applications.

Developing and integrating LLM-powered systems.

Designing RAG pipelines and intelligent knowledge systems.

Building Agentic AI and multi-agent workflows.

Working with computer vision, NLP and deep learning.

Model evaluation, optimization and deployment.

Cloud-based AI application development.

API engineering and full-stack AI integration.

Git collaboration, software architecture and engineering practices.

Working on practical product and client-oriented requirements.

Who Should Apply?

We welcome applications from

B.Tech / B.E. students in Computer Science, IT, AI/ML, Electronics or related disciplines.

MCA, M.Sc. Computer Science, Data Science and related students.

Recent graduates and freshers interested in AI engineering.

Candidates with personal, academic or open-source AI/ML projects.

Developers interested in transitioning into Generative AI and intelligent automation.

Ideal candidates are

Comfortable with Python and programming fundamentals.

Familiar with basic Machine Learning concepts.

Interested in experimenting with new AI frameworks and models.

Capable of researching, debugging and solving technical problems.

Willing to learn independently and collaborate with a development team.

Internship Details & Benefits

Stipend ₹10,000 per month, depending on skills and selection.

Flexible internship duration of 2–6 months.

Remote work opportunities across India.

Flexible working schedule.

Hands-on exposure to real-world software and AI projects.

Mentorship and technical collaboration.

Opportunity to contribute to live product development and client-oriented assignments.

Internship Completion Certificate upon successful completion.

Letter of Recommendation based on performance and contribution.

Potential consideration for extended or full-time opportunities based on performance and business requirements.

Application Process

Interested candidates should submit

Updated resume (PDF).

GitHub profile (preferred).

LinkedIn profile (optional).

Links t