Machine Learning Architect, Data

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🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

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Coretek

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

🏥 Healthcare

🏭 Manufacturing

Consulting • Healthcare • Manufacturing

Coretek is a nationally recognized Microsoft Azure Expert Managed Service Provider (MSP) and the number one Microsoft Cloud Solution Provider in the United States. The company specializes in providing cloud solutions, security services, and AI-driven innovations to a wide range of industries, including government, healthcare, manufacturing, and financial services. Coretek offers a variety of services such as cloud migration, app modernization, DevOps automation, and workspace management. They are known for their comprehensive security solutions, leveraging platforms like Palo Alto and Dynatrace, and their partnerships with companies like Imprivata and Citrix. Coretek's expertise extends to Azure OpenAI services, making them a leader in delivering innovative AI and machine learning solutions. Their commitment to technology excellence has earned them a spot on the Inc. 5000 list of fastest-growing private companies and recognition as a Microsoft Partner of the Year finalist.

📋 Description

• Own end-to-end technical architecture for machine learning and AI engagements, from target-state design through production acceptance • Define reference architectures for Fabric-first data science and MLOps platforms, including environment topology, storage boundaries, and promotion paths • Produce architecture decision records, requirements traceability, and design documentation for security and compliance review • Make platform tradeoff decisions across Fabric, Azure-native services, managed/custom components, and build/configure options • Define compute sizing, cost guardrails, and capacity planning for batch and inference workloads • Establish third-party and open-source governance patterns • Architect sandbox, development/staging, and production environments with isolation and role-based access • Design governed data access, data science write-back boundaries, and reusable batch prediction and forecasting pipelines • Design CI/CD, promotion, orchestration, scheduling, data quality gates, versioning, observability, drift monitoring, backup, recovery, and retention architectures • Architect production generative AI and LLM solutions using Azure OpenAI, retrieval-augmented generation, agents, evaluation, guardrails, and LLMOps practices • Design solutions across Microsoft Fabric and integrations with Azure Machine Learning, Azure OpenAI, Azure AI Search, Databricks, Data Factory, Cosmos DB, and Azure Storage • Define identity, networking, security, compliance, performance, reliability, and observability architecture • Serve as senior technical voice in client design sessions and workshops • Advise clients on AI and data platform roadmaps, platform selection, and investment sequencing • Lead knowledge transfer and operational handoff • Provide technical direction, design and code review, mentoring, solution documentation, reusable accelerators, and internal reference architectures

🎯 Requirements

• 5+ years of professional experience in data, machine learning, or AI engineering, including 3+ years in solution architecture or lead technical design • Demonstrated ownership of monitored, scheduled production machine learning systems 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 beyond proof of concept • Strong Python and SQL • Deep MLOps expertise in lifecycle management, versioning, reproducibility, evaluation, monitoring, drift detection, and retraining strategy • CI/CD and automation experience with Azure DevOps or GitHub Actions for data, notebook, and model assets • Working command of Entra ID, managed identities, service principals, Key Vault, and RBAC • Experience architecting orchestration, scheduling, and data quality validation for production pipelines • Excellent written and verbal communication skills for executive and technical audiences • 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 • Preferred: production-scale time-series forecasting; experimentation platforms; MLflow; R, renv, Great Expectations or Soda; Bicep or Terraform; Spark; Power BI and semantic modeling; Azure certifications; consulting/professional services; regulated or security-reviewed environments

🏖️ Benefits

• 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 • Ownership of architecture on high-impact, real-world engagements across multiple industries