Strategic ML Platform Architect on Google Cloud

Spyro Soft; Poland; Remote; USD 180,000 - 240,000; Full time

Job summary

Spyro Soft is seeking a Lead ML Architect to define target architectures for enterprise ML and MLOps platforms on Google Cloud. You will drive architecture workshops with enterprise stakeholders and translate requirements into scalable, secure designs across data, security and operations.

You will lead end-to-end ML lifecycle patterns, governance, feature management, and integration with CI/CD, IAM, and data ecosystems, ensuring scalable, reusable pipelines and strong production readiness.

Qualifications

• Proven experience designing and delivering production-grade ML and MLOps platforms in enterprise environments
• Deep hands-on expertise with Google Cloud Platform (GCP)
• Strong production experience with Vertex AI and Gemini Enterprise Platform Pipelines
• Proven ability to design end-to-end ML lifecycle architectures and pipeline orchestration frameworks
• Strong understanding of modular, reusable and scalable ML pipeline design patterns
• Extensive knowledge of BigQuery and its role within enterprise-scale Machine Learning ecosystems
• Practical experience with ML lifecycle management, model monitoring, retraining strategies, rollback mechanisms and reproducibility standards
• Hands-on experience designing CI/CD and deployment patterns for ML solutions
• Experience building solutions that operate across development, testing and production environments
• Strong understanding of cloud security, IAM, governance and compliance principles
• Solid software engineering background with architectural mindset
• Ability to evaluate architecture trade-offs related to scalability, security, maintainability, operability and cost optimization
• Experience working directly with enterprise customers and senior technical stakeholders
• Excellent communication skills and the ability to facilitate architecture workshops and technical discussions
• Ability to operate comfortably between strategic architecture planning and implementation-level engineering details
• Fluent English (C1) and strong Polish communication skills (minimum B2), both written and verbal

Responsibilities

• Own the target architecture of enterprise ML and MLOps platforms on Google Cloud
• Lead architecture workshops, discovery sessions and technical discussions with enterprise customers
• Translate business, ML, data, security and operational requirements into scalable architecture designs
• Design end-to-end Machine Learning lifecycle patterns covering data preparation, feature engineering, experimentation, model training, evaluation, model registration and promotion
• Define architecture standards and best practices for Vertex AI and Gemini Enterprise Agent Platform Pipelines
• Design reusable and modular pipeline architectures supporting multiple teams and ML workloads
• Define governance frameworks including approval processes, lifecycle policies, lineage tracking and reproducibility standards
• Design feature management solutions leveraging BigQuery and Google Cloud-native services
• Establish integration patterns between ML platforms, enterprise data ecosystems, CI/CD frameworks, IAM and governance solutions
• Define monitoring strategies covering model performance, drift detection, observability and ground-truth validation
• Provide architectural guidance to MLOps, Cloud and Data Engineering teams throughout implementation
• Drive technical decision-making and ensure alignment with enterprise architecture standards
• Maintain architecture documentation, technology roadmaps and implementation guidelines
• Promote engineering excellence and adoption of cloud-native Machine Learning best practices across the organization

Skills

ML architecture

Cloud architecture

Enterprise engagement

Communication skills

Security & governance understanding

Tools

GCP

Vertex AI

Gemini Platform Pipelines

BigQuery

Terraform

CI/CD

Kubernetes (GKE)

Dataflow

IAM

Model Registry

Monitoring & Observability

Python

Job description

Spyro Soft is seeking a Lead ML Architect to define target architectures for enterprise ML and MLOps platforms on Google Cloud. You will drive architecture workshops with enterprise stakeholders and translate requirements into scalable, secure designs across data, security and operations.

You will lead end-to-end ML lifecycle patterns, governance, feature management, and integration with CI/CD, IAM, and data ecosystems, ensuring scalable, reusable pipelines and strong production readiness.