AI Engineer 2

Atlassian; Bengaluru; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Atlassian in Bengaluru, India, is seeking a skilled AI/ML/NLP engineer with 3-6 years of hands-on experience to advance cutting-edge language models.

You will master Python, transformer architectures, and modern DL frameworks, building and deploying models with PyTorch or TensorFlow, Hugging Face tools, and MLOps practices. This role emphasizes scalability on cloud platforms and containerized deployments.

Qualifications

• 3-6 years hands-on experience in AI/ML/NLP.
• Strong programming expertise in Python.
• Solid understanding of NLP fundamentals and Transformer architectures.
• Hands-on experience in building, fine-tuning, optimising, and deploying deep learning models, including transformer-based models.
• Strong foundations in Computer Science, Machine Learning, Deep Learning, and software engineering principles.
• Experience with PyTorch and/or TensorFlow.
• Proficiency with Hugging Face Transformers, model training pipelines, and evaluation techniques.
• Experience with Large Language Models (LLMs), embeddings, Retrieval-Augmented Generation (RAG), vector databases, and prompt engineering.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and model deployment using Docker/Kubernetes.
• Experience with version control, CI/CD pipelines, and MLOps practices.

Skills

Python

NLP

Transformer models

PyTorch

TensorFlow

Hugging Face

LLMs

RAG

Vector databases

Prompt engineering

Cloud platforms

Docker

Kubernetes

MLOps

CI/CD

Tools

PyTorch

TensorFlow

Hugging Face

Docker

Kubernetes

Job description

Requirements:

• 3-6 years of hands-on experience in AI, Machine Learning, or NLP.


• Strong programming expertise in Python.


• Solid understanding of Natural Language Processing (NLP) fundamentals and Transformer architectures.


• Hands-on experience in building, fine-tuning, optimising, and deploying deep learning models, including transformer-based models.


• Strong foundations in Computer Science, Machine Learning, Deep Learning, and software engineering principles.


• Experience with PyTorch and/or TensorFlow.


• Proficiency with Hugging Face Transformers, model training pipelines, and evaluation techniques.


• Experience with Large Language Models (LLMs), embeddings, Retrieval-Augmented Generation (RAG), vector databases, and prompt engineering.


• Familiarity with cloud platforms (AWS, Azure, or GCP) and model deployment using Docker/Kubernetes.


• Experience with version control, CI/CD pipelines, and MLOps practices.