Position - 01
Job Location - Ahmedabad
Qualification - Graduate
Working Hours - Full Time
Years of Exp - 0 to 1 Year

About us

We’re looking for a curious, driven, and hands-on Junior AI/ML Developer who is excited to turn ideas into intelligent solutions. You’ll get the prospect to work at the intersection of Large Language Models (LLMs), Computer Vision, and Deep Learning, contributing to projects that push the boundaries of what AI can do. The ideal candidate has a strong grasp of deep learning concepts, neural networks, and machine learning fundamentals, along with practical experience in building and working with data pipelines.

Roles & responsibilities
Support development and fine-tuning of Large Language Models (LLMs) using open-source or proprietary models (e.g., OpenAI, HuggingFace, LLaMA).
Build and optimize Computer Vision pipelines for tasks such as object detection, image classification, and OCR.
Design and implement data preprocessing pipelines, including handling structured and unstructured data.
Assist in training, evaluation, and deployment of ML/DL models in staging or production environments.
Write clean, scalable,



and well-documented code for research and experimentation purposes.
Collaborate with senior data scientists, ML engineers, and product teams on AI projects.

Skills required
Robust foundation in Neural Networks, Deep Learning, and ML algorithms.
Hands-on experience with Python and libraries such as TensorFlow, PyTorch, OpenCV, or HuggingFace Transformers.
Familiarity with LLM architectures (e.g., GPT, BERT, LLaMA) and their fine-tuning or inference techniques.
Basic understanding of Computer Vision concepts and real-world use cases.
Experience working with data pipelines and handling large datasets (e.g., Pandas, NumPy, data loaders).
Knowledge of model evaluation techniques and metrics.

Valuable to Have
Experience using Hugging Face, LangChain, OpenCV, or YOLO for CV tasks.
Familiarity with Prompt Engineering and Retrieval-Augmented Generation (RAG).
Understanding of NLP concepts such as tokenization, embeddings, and vector search.
Exposure to ML model deployment (Flask, FastAPI, Streamlit, or AWS/GCP/Azure).
Participation in ML competitions (e.g., Kaggle) or personal projects on GitHub.

📌 Junior Ai Ml Developer Ahmedabad
🏢 Bytes Technolab
📍 Ahmedabad