■Job Overview
We are seeking a highly skilled AI/ML Engineer to design, develop, and deploy advanced predictive models and LLM-based applications, including Retrieval-Augmented Generation (RAG) systems, on the Azure ecosystem.
The ideal candidate will work closely with data engineering and platform teams to build scalable, production-grade AI solutions leveraging Azure Machine Learning, Azure OpenAI Service, and Azure AI Foundry. This role requires strong expertise in cloud-native AI architecture, data engineering integration, and MLOps practices.
■Key Responsibilities
1. Model Development
- Design, train, fine-tune, and deploy predictive models and LLM-based applications.
- Build and operationalize RAG pipelines using Azure AI services.
- Work with Azure Machine Learning and Azure AI Foundry for model lifecycle management.
2. Data Integration
- Collaborate with data engineering teams to consume large-scale datasets from Azure Data Lake Storage (ADLS) and Azure Synapse Analytics.
- Process and analyze structured and semi-structured data formats including Parquet, CSV, and text datasets.
3. Application Architecture
- Develop serverless AI orchestration layers using Azure Functions.
- Integrate AI models with downstream applications and APIs for real-time inference.
4. Storage & Retrieval Optimization
- Implement intelligent retrieval systems using Azure AI Search for low-latency query processing.
- Optimize storage strategies for metadata, embeddings, and AI outputs.
5. Operational Excellence (MLOps)
- Implement end-to-end MLOps pipelines for training, deployment, monitoring, and retraining.
- Integrate AI workflows into CI/CD pipelines using Azure DevOps or GitHub Actions.
- Ensure scalability, reliability, and reproducibility of AI systems in production.
■Requirements
・Technical Requirements
Azure AI Stack
Hands-on experience with:
Azure Machine Learning
Azure AI Foundry
Azure OpenAI Service
Data Engineering & Storage
Strong understanding of:
- Azure Data Lake Storage (ADLS)
- Azure Synapse Analytics
- Experience handling large-scale datasets and Parquet file formats
- Programming & Data Processing
- Strong proficiency in Python for AI/ML development
- Familiarity with Scala and Apache Spark for large-scale ETL processing
- Backend & NoSQL Systems
- Experience building APIs using Azure Functions
- Knowledge of CosmosDB or other NoSQL databases
- DevOps & Automation
- Experience with CI/CD pipelines using Azure DevOps or GitHub Actions
- Understanding of automated model deployment and lifecycle management
Preferred Qualifications
- Experience in Insurance or Financial Services domains
- Proven ability to derive business insights from complex customer datasets
- Hands-on experience building Retrieval-Augmented Generation (RAG) systems
- Familiarity with Azure Databricks and distributed data processing
■Industry
Software / Information Processing
■Expected Annual Salary
8 Million JPY - 10 Million JPY
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We look forward to your application.