AI Engineer (Fresher / Entry-Level)

As an Entry-Level AI Engineer, you will work with experienced engineers and data scientists to design, develop, and deploy AI-powered solutions.

You will contribute to building conversational AI systems, intelligent automation workflows, Retrieval-Augmented Generation (RAG) pipelines, and machine learning applications that enhance customer support experiences.

This role is ideal for candidates with a strong foundation in Python, Natural Language Processing (NLP), Generative AI, and MLOps who are excited about solving real-world problems using AI technologies.

Responsibilities

• Develop and maintain AI/ML applications using Python.
• Build and optimise NLP pipelines for text processing, classification, information extraction, and semantic search.
• Develop Generative AI solutions using Large Language Models (LLMs).
• Implement Retrieval-Augmented Generation (RAG) systems using vector databases and embedding models.
• Design prompts and evaluate LLM responses for quality and performance.
• Collaborate with senior engineers to deploy and monitor AI applications in production.
• Build APIs and AI services using frameworks such as FastAPI.
• Assist in model training, fine-tuning, evaluation, and experimentation.
• Work with MLOps tools to automate model deployment, monitoring, and versioning.
• Participate in code reviews, testing, debugging, and documentation activities.
• Stay up-to-date with emerging AI, NLP, and Generative AI technologies.

Requirements

Technical Skills

• Strong programming skills in Python.
• Understanding of Data Structures and Algorithms.
• Knowledge of Machine Learning fundamentals.
• Understanding of Natural Language Processing (NLP) concepts:
• Tokenisation
• Embeddings
• Text Classification
• Named Entity Recognition (NER)
• Semantic Search
• Transformer Models

• Understanding of Generative AI concepts:
• Large Language Models (LLMs)
• Prompt Engineering
• RAG (Retrieval-Augmented Generation)
• Fine-tuning concepts
• AI Agent fundamentals

• Familiarity with AI/ML frameworks:
• PyTorch or TensorFlow
• Hugging Face Transformers
• LangChain, LlamaIndex, or similar frameworks

MLOps Knowledge

• Understanding of model deployment and serving concepts.
• Familiarity with:
• Docker
• Git/GitHub
• CI/CD concepts
• Kubernetes (basic understanding)
• ML experiment tracking tools (MLflow, Weights & Biases, etc.)

Database & API Skills

• Basic knowledge of SQL databases.
• Familiarity with vector databases such as Pinecone, Weaviate, Qdrant, or ChromaDB.
• Understanding of REST APIs and FastAPI.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
• Hands-on academic projects, internships, or personal projects in AI/ML.
• Experience building chatbots, AI assistants, or NLP applications.
• Contributions to open-source AI projects are a plus.
• Familiarity with cloud platforms such as AWS, GCP, or Azure.

What We Look For

• Strong problem-solving and analytical skills.
• Passion for AI, Machine Learning, and emerging technologies.
• Curiosity to learn and experiment with new AI frameworks and tools.
• Good communication and teamwork skills.
• Ability to work in a fast-paced, collaborative environment.

Nice-to-Have Projects

Candidates who have built any of the following will stand out:

• AI Chatbot using LLMs
• RAG-based Question Answering System
• AI Agent using LangChain or LlamaIndex
• Document Search and Retrieval Platform
• Customer Support Automation Bot
• NLP Classification or Information Extraction System
• End-to-End ML Deployment Project with Docker/Kubernetes

Benefits

• Hybrid setup
• Worker's insurance
• Paid Time Offs
• Other employee benefits to be discussed by our Talent Acquisition team in India.