GCP Machine Learning

In this role, you will be responsible for Machine Learning & Deep Learning, NLP (semantic search, text generation), AI solution architecture, and Python-based AI/ML development. Your main tasks will involve hands-on model building and deployment, MLOps/AIOps, working with cloud platforms (Azure/AWS/GCP), GenAI & LLM engineering (RAG, autonomous agents), containerisation (Docker, Kubernetes), AI governance & ethics, stakeholder collaboration, mentoring, and providing technical leadership. Key Responsibilities: - Develop Machine Learning & Deep Learning models - Implement NLP techniques such as semantic search and text generation - Design AI solution architectures - Work on Python-based AI/ML development - Deploy models using MLOps/AIOps practices - Utilize cloud platforms like Azure, AWS, and GCP - Engage in GenAI & LLM engineering, including RAG and autonomous agents - Containerize applications using Docker and Kubernetes - Ensure AI governance and ethics are followed - Collaborate with stakeholders - Mentor team members and provide technical leadership Qualifications Required: - Solid experience in AI/ML solution architecture - Proficiency in GenAI & LLM engineering, including LangChain/LangGraph, RAG, and autonomous agents - Expertise in Machine Learning & Deep Learning - Familiarity with NLP techniques such as semantic search, entity recognition, and text generation - Ability to design and deploy cloud-native AI solutions (Note: Additional details of the company were not included in the provided job description.) In this role, you will be responsible for Machine Learning & Deep Learning, NLP (semantic search, text generation), AI solution architecture, and Python-based AI/ML development. Your main tasks will involve hands-on model building and deployment, MLOps/AIOps, working with cloud platforms (Azure/AWS/GCP), GenAI & LLM engineering (RAG, autonomous agents), containerisation (Docker, Kubernetes), AI governance & ethics, stakeholder collaboration, mentoring, and providing technical leadership. Key Responsibilities: - Develop Machine Learning & Deep Learning models - Implement NLP techniques such as semantic search and text generation - Design AI solution architectures - Work on Python-based AI/ML development - Deploy models using MLOps/AIOps practices - Utilize cloud platforms like Azure, AWS, and GCP - Engage in GenAI & LLM engineering, including RAG and autonomous agents - Containerize applications using Docker and Kubernetes - Ensure AI governance and ethics are followed - Collaborate with stakeholders - Mentor team members and provide technical leadership Qualifications Required: - Solid experience in AI/ML solution architecture - Proficiency in GenAI & LLM engineering, including LangChain/LangGraph, RAG, and autonomous agents - Expertise in Machine Learning & Deep Learning - Familiarity with NLP techniques such as semantic search, entity recognition, and text generation - Ability to design and deploy cloud-native AI solutions (Note: Additional details of the company were not included in the provided job description.)