Architect - Machine Learning and Data

Role Description

Coretek is seeking an Architect, Machine Learning and Data to lead the design of production machine learning and generative AI platforms on Microsoft Azure and Microsoft Fabric. This role sits at the point where data platform architecture, MLOps, and applied AI meet. You will define how client organizations move models out of notebooks and into governed, monitored, reproducible production operation, and how generative AI capabilities are architected to be secure, evaluable, and cost-controlled at enterprise scale.

You will own the technical architecture on client engagements end to end:

• Target-state design
• Environment and identity models
• Pipeline and promotion patterns
• Observability standards
• Operational handoff that lets a client run the platform without you

You will work alongside data scientists, data engineers, and delivery leadership, translating requirements into architecture decisions and then staying close enough to implementation to be accountable for the result. This is a delivery architecture role. Depth of production experience matters more than breadth of exposure, and the expectation is that you have personally been responsible for systems that ran unattended and were handed to someone else to operate.

Qualifications

• 5+ years of professional experience in data, machine learning, or AI engineering, including 3+ years in a solution architecture or lead technical design capacity.
• Demonstrated ownership of production machine learning systems, meaning systems that executed on a schedule, were monitored, and were operated by someone other than the author.
• Hands-on architecture experience with Microsoft Azure data and AI services, including Microsoft Fabric and lakehouse architectures.
• Production generative AI experience, including large language model solutions, retrieval-augmented generation, and prompt-based workflows deployed beyond proof of concept.
• Strong Python and SQL, sufficient to review and correct the work of senior engineers.
• Deep MLOps expertise: model lifecycle management, versioning, reproducibility, evaluation, monitoring, drift detection, and retraining strategy.
• CI/CD and automation experience with Azure DevOps or GitHub Actions applied to data, notebook, and model assets.
• Working command of Azure identity and security: Entra ID, managed identities, service principals, Key Vault, and RBAC, including designing workloads that run without user-bound authentication.
• Experience architecting orchestration, scheduling, and data quality validation for production pipelines.
• Excellent written and verbal communication, with the ability to present architecture to executive stakeholders and defend it under technical challenge.
• Ability to manage technical scope, priorities, and expectations across concurrent engagements.
• Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or a related quantitative discipline. Master's degree preferred.

Requirements

• Experience with time-series forecasting at production scale, including rolling origin evaluation and horizon-based output design.
• Experimentation platform design: treatment assignment, matched datasets, causal inference methods, and result storage.
• Familiarity with MLflow, experiment tracking, and prompt and version management tooling.
• Working knowledge of R in a platform context, including renv and executing client-provided R workloads on a schedule.
• Experience with data quality frameworks such as Great Expectations or Soda.
• Infrastructure as Code with Bicep or Terraform.
• Spark-based processing in Databricks or Fabric.
• Power BI and semantic modeling depth.
• Azure certifications such as Azure Solutions Architect Expert (AZ-305), Fabric Data Engineer Associate (DP-700), Fabric Analytics Engineer Associate (DP-600), Azure Data Scientist Associate (DP-100), Azure AI Engineer Associate (AI-102), or Azure Data Engineer Associate (DP-203).
• Consulting or professional services background, delivering to fixed scope and milestone acceptance.
• Experience in regulated or security-reviewed environments where architecture is subject to formal review.

Benefits

• Microsoft Azure Expert Partner delivering advanced AI, Generative AI, Data, and Fabric solutions.
• Ownership of architecture on high-impact, real-world engagements across multiple industries.
• Strong emphasis on learning, innovation, and technical leadership.
• Collaborative, remote-first consulting culture with experienced architects and practitioners.
• Direct exposure to the full AI lifecycle, from strategy and design through production and optimization.