全职 GenAI Architect 工作, 薪水, RiDiK (a Subsidiary Of CLPS. Nasdaq: CLPS) 公司招聘中 - Ricebowl

Job Title: GenAI Architect – Data Science & Machine Learning

Location:Singapore (Onsite)

Experience:10+ Years

Job Summary:

We are seeking an experienced GenAI Architect with a strong background in Data Science, Machine Learning, and Generative AI. The ideal candidate will lead the design, architecture, and implementation of enterprise-scale AI solutions leveraging Large Language Models (LLMs), Machine Learning frameworks, and cloud-native AI platforms.

Key Responsibilities:

• Design and implement end-to-end Generative AI solutions using LLMs and foundation models.
• Define AI/ML architecture, governance, security, and scalability standards.
• Lead the development of AI-powered applications including RAG, AI Agents, chatbots, and intelligent automation solutions.
• Collaborate with Data Scientists, ML Engineers, Product Owners, and Business Stakeholders to translate business requirements into AI solutions.
• Build and optimize Machine Learning pipelines for training, deployment, monitoring, and retraining.
• Architect data platforms to support AI workloads, feature engineering, and model serving.
• Evaluate and integrate AI technologies such as OpenAI, Anthropic, Gemini, Llama, Mistral, and other foundation models.
• Drive MLOps and LLMOps best practices for model lifecycle management.
• Ensure responsible AI practices including explainability, governance, privacy, and compliance.
• Mentor technical teams and provide architectural leadership for AI initiatives.

Required Skills:

• Strong experience in Generative AI, Data Science, and Machine Learning.
• Expertise in Large Language Models (LLMs) and foundation models.
• Experience with RAG (Retrieval-Augmented Generation), Vector Databases, AI Agents, and Prompt Engineering.
• Strong proficiency in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, Hugging Face.
• Experience with cloud platforms:
• AWS (Bedrock, SageMaker)
• Azure (Azure OpenAI, ML Studio)
• GCP (Vertex AI)
• Experience with MLOps/LLMOps tools.
• Knowledge of data engineering, data lakes, and distributed computing frameworks.
• Strong understanding of NLP, Deep Learning, and AI model evaluation techniques.

Preferred Skills:

• Experience implementing enterprise AI solutions at scale.
• Knowledge of Agentic AI frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel.
• Experience with Vector Databases such as Pinecone, Weaviate, ChromaDB, or FAISS.
• Exposure to Responsible AI and AI Governance frameworks.
• Experience in Banking, Financial Services, Healthcare, Manufacturing, or Retail domains.