JALANDHAR · FULLTIME
AI / ML Engineer - Intern
Pradrix
Jalandhar · onsite · Posted 20d ago
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Section · 01
About this role
We are looking for an AI/ML Engineer Intern who is interested in building practical AI/ML solutions and experimenting with modern AI technologies. You will work on projects involving machine learning, LLMs, RAG, embeddings, AI agents, automation, APIs, and AI-powered applications. This role is suitable for someone who has a good foundation in Python and machine learning and wants to gain practical experience by working on real products and business use cases. You don't need to know every technology listed below. Strong fundamentals, curiosity, and the ability to learn independently are more important.
Responsibilities:
- Build and integrate AI/ML solutions for real-world use cases.
- Work with LLMs, embeddings, RAG pipelines, vector databases, and AI agents.
- Experiment with different models, prompts, retrieval strategies, and AI workflows.
- Build prototypes and turn successful experiments into working features.
- Work with frameworks such as LangChain, LangGraph, Hugging Face, or similar tools.
- Prepare, process, and analyze data for ML/AI applications.
- Develop and integrate APIs for AI/ML functionality.
- Evaluate model outputs and improve accuracy, reliability, and performance.
- Research new AI models, frameworks, and tools and evaluate where they can be useful.
- Debug, test, document, and improve AI systems.
- Collaborate with developers and other team members on product development.
Requirements:
- Strong understanding of Python.
- Basic understanding of machine learning concepts.
- Familiarity with Pandas, NumPy, and Scikit-learn.
- Understanding of basic data processing and model evaluation.
- Familiarity with Git/GitHub.
- Ability to understand technical documentation and learn new technologies independently.
- Good problem-solving skills.
- Good to have: Experience with one or more of PyTorch / TensorFlow, Hugging Face, LLM APIs, RAG, embeddings, vector databases, LangChain, LangGraph, AI agents, FastAPI / Flask, PostgreSQL, Docker, and cloud platforms such as AWS.
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Section · 02