Data Science Engineer – Generative AI & Machine Learning

About the Company

We are seeking a highly skilled Data Science Engineer with strong expertise in Machine Learning and Generative AI technologies. The ideal candidate will have hands-on experience in designing, developing, deploying, and monitoring machine learning models, along with practical exposure to Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG) solutions.

About the Role

We are seeking a highly skilled Data Science Engineer with strong expertise in Machine Learning and Generative AI technologies.

Responsibilities

• Design, develop, and deploy scalable Machine Learning and Generative AI solutions.
• Build and optimize end-to-end ML pipelines.
• Develop and maintain RAG-based applications leveraging LLMs.
• Collaborate with cross-functional teams to translate business requirements into AI-driven solutions.
• Monitor model performance and implement continuous improvements.
• Ensure best practices in model governance, deployment, and observability.

Qualifications

• Total experience of 7+ years in Data Science, Machine Learning, or AI-related roles.
• Minimum 5+ years of hands-on experience in Machine Learning.
• 6 months to 2 years of practical experience working on Generative AI and LLM-based solutions.

Required Skills

• Strong programming expertise in Python.
• Strong SQL skills for data analysis and data processing.
• Experience working with Google Cloud Platform (GCP).
• Experience in Machine Learning model development, training, validation, deployment, and monitoring.
• Strong understanding of supervised and unsupervised learning techniques.
• Experience with ML frameworks and data science libraries.
• Hands-on experience with Large Language Models (LLMs).
• Strong understanding of Prompt Engineering techniques.
• Experience building Retrieval-Augmented Generation (RAG) solutions.
• Knowledge of vector databases, embeddings, and LLM orchestration frameworks is an added advantage.

Preferred Skills

• Experience with MLOps practices and CI/CD pipelines.
• Exposure to AI/ML solutions on cloud platforms.
• Strong problem-solving and analytical skills.
• Excellent communication and stakeholder management abilities.