Junior Data Scientist

We are looking for a highly skilled

AI/ML/Gen AI Data Scientist

with expertise in

Generative AI, Machine Learning, Deep Learning, and Natural Language Processing (NLP)

. The ideal candidate should have a strong foundation in

Python-based AI frameworks

and experience in developing, deploying, and optimizing AI models for real-world applications.

Key Responsibilities

Develop and implement AI/ML models

.Work with

Deep Learning architectures

like Transformers (BERT, GPT, LLaMA) and CNNs/RNNs.Fine-tune and optimize

Large Language Models (LLMs)

for various applications.Design and train

custom Machine Learning models

using

structured

and unstructured data.Leverage

NLP techniques

such as text summarization, Named Entity Recognition (NER).Implement

ML pipelines

and deploy models in cloud environments (AWS/GCP/Azure).Collaborate with cross-functional teams to integrate AI-driven solutions into business applications.Stay updated with

latest AI advancements

and apply innovative techniques to improve model performance.

Required Skills & Qualifications

1 to 3 years

of experience in

AI/ML, Deep Learning, and Generative AI

.Strong proficiency in

Python

and ML frameworks like

TensorFlow, PyTorch, Hugging Face, Scikit-learn

.Hands-on experience with

NLP models

, including

BERT, GPT, T5, LLaMA, and Stable Diffusion

.Expertise in

data preprocessing, feature engineering, and model evaluation

.Experience with

MLOps, cloud-based AI deployment, and containerization (Docker, Kubernetes)

.Knowledge of

vector databases

and

retrieval-augmented generation (RAG)

techniques.Ability to

fine-tune LLMs

and work with

prompt engineering

.Strong problem-solving skills and ability to work in

agile environments

.

Educational Requirements

Bachelor's, Master's, or PhD

in

Computer Science/Artificial Intelligence/Information Technology

Preferred Skills (Good To Have)

Experience with

Reinforcement Learning (RLHF)

and

multi-modal AI

.Familiarity with

AutoML, Responsible AI (RAI), and AI Ethics

.Exposure to

Graph Neural Networks (GNNs)

and time-series forecasting.Contributions to

open-source AI projects

or research papers.Skills:- Machine Learning (ML), Generative AI, Artificial Intelligence (AI), Python and Large Language Models (LLM)