Architect - Machine Learning and Data
USD 175K-223K (estimate) Senior-level Full Time
Tasks
- Architect backup recovery and retention for model artifacts
- Architect batch prediction and forecasting pipeline patterns
- Architect experimentation platform patterns and evaluation metrics
- Architect integrations across Azure Machine Learning Azure OpenAI and Azure AI Search
- Architect production generative AI solutions on Azure OpenAI
- Architect sandbox staging and production environment models with isolation
- Author solution designs runbooks and reusable delivery accelerators
- Create architecture decision records and technical design documentation
- Define chunking embedding indexing and reranking strategies
- Define compute sizing assumptions and cost guardrails
- Define identity networking and security architecture using Entra ID Key Vault and RBAC
- Define inference and orchestration patterns for API serverless and containers
- Define observability and drift monitoring architecture
- Define orchestration and scheduling patterns with failure visibility
- Define reference architectures for Fabric first data science and MLOps platforms
- Design data quality gates for schema validation and anomaly detection
- Design forecasting specific time series scoring patterns
- Design governed access to enterprise data warehouse sources
- Design guardrails and responsible AI controls including PII handling
- Design observability for generative systems including tracing and cost attribution
- Design retrieval augmented generation architectures and vector store selection
- Design solutions across Microsoft Fabric Lakehouse Warehouse Notebooks Data Pipelines and semantic models
- Ensure downstream consumption patterns including Power BI semantic layer design
- Establish LLMOps prompt version management and automated evaluation
- Establish data governance patterns for third party and open source dependencies
- Establish versioning standards for code environment and data references
- Implement CI CD promotion architecture for notebooks and platform assets
- Implement agent and multi agent solutions with tool boundaries
- Implement headless execution using managed identities and Key Vault
- Implement token cost and model selection and caching strategies
- Lead client design sessions workshops and architecture advisory
- Lead end to end machine learning and AI solution architecture
- Make platform tradeoff decisions for Fabric versus Azure services
- Provide technical direction mentoring and code and design reviews
Perks/Benefits
- N/A
Skills/Tech-stack
AI Search | Autogen | Azure AI | Azure AI Search | Azure Data | Azure Data Factory | Azure Database | Azure Database for PostgreSQL | Azure Databricks | Azure DevOps | Azure Key Vault | Azure Machine Learning | Azure OpenAI | Azure Storage | CI/CD | Cosmos DB | Data Factory | Data Quality | Database for PostgreSQL | Deployment Pipelines | Drift Detection | Entra ID | Generative AI | Git | GitHub Actions | Key Vault | MLOps | Machine Learning | Managed Identity | Microsoft Fabric | Model Monitoring | Observability | PGVector | Pydantic | Python | RBAC | Retrieval-Augmented Generation | SQL | Semantic Kernel | Series forecasting | Time Series | Time Series Forecasting | Vector Databases
Education
N/A
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