Data Science Engineer Generative AI & Machine Learning

Job Description

As a highly skilled Data Science Engineer specializing in Machine Learning and Generative AI technologies, you will be responsible for designing, developing, deploying, and monitoring machine learning models. Your expertise in Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG) solutions will be crucial for the role.**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 As a highly skilled Data Science Engineer specializing in Machine Learning and Generative AI technologies, you will be responsible for designing, developing, deploying, and monitoring machine learning models. Your expertise in Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG) solutions will be crucial for the role.**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

Keyskills :
PythonSQLMachine LearningAnalytical skillsCommunicationStakeholder managementGoogle Cloud Platform GCPLarge Language Models LLMsPrompt EngineeringRetrievalAugmented Generation RAGML frameworksData Science librariesVector databasesEmbeddings