Job Description

Location:
(Onsite / Hybrid / Remote - as per requirement)

Job Type: Contract / Full-time

We are seeking a Hybrid Cloud MLOps Architect with strong consulting expertise to lead a client-facing engagement and provide strategic direction across machine learning operations, cloud architecture, and enterprise-scale deployment models. The ideal architect will act as a trusted advisor, driving end-to-end MLOps architecture, hybrid-cloud integration, and operational excellence across data science and engineering teams.

This role requires deep technical knowledge, architectural leadership, and the ability to influence business and IT stakeholders to build scalable, secure, and high-performance ML platforms.

• Define and lead the Hybrid-Cloud MLOps architectural vision , aligning with the client's AI/ML strategy, cloud roadmap, and enterprise technology goals.

• Design end-to-end MLOps architectures spanning model development, training, deployment, monitoring, governance, and lifecycle management.

• Architect scalable ML pipelines across on-prem and multi-cloud platforms (AWS / Azure / GCP).

• Act as a solo consulting architect , working directly with client leadership to assess their current MLOps maturity, identify gaps, and build a transformation roadmap.

• Provide hands-on guidance on ML governance, CI/CD for ML, model registry frameworks, feature stores, and monitoring strategies .

• Lead workshops, strategy discussions, and solution reviews with data science, engineering, DevOps, and cloud teams.

• Develop solution frameworks, reference architectures, and operational models for hybrid-cloud ML workflows.

• Oversee PoCs, platform evaluations, and integration strategies to ensure scalability, performance, security, and compliance.

• Act as the primary architectural decision-maker throughout implementation and troubleshoot complex MLOps challenges.

• Mentor internal client teams on best practices in ML orchestration, model deployment automation, and hybrid-cloud infrastructure.

• Stay current with evolving cloud-native and MLOps technologies to guide clients on continuous innovation.

• Produce high-quality architecture artifacts - including architecture blueprints, workflow diagrams, integration patterns, governance frameworks, and platform documentation.

• Ensure all MLOps pipelines adhere to robust governance, observability, and performance standards.

• 7+ years of experience in MLOps, ML Engineering, Cloud Architecture, or related roles.

• Proven experience architecting ML platforms across hybrid cloud environments (on-prem + AWS/Azure/GCP).

• Strong expertise in:

  • ML lifecycle orchestration (MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML)

  • CI/CD & IaC (GitHub Actions, Jenkins, Argo, Terraform, CloudFormation)

  • Containerization & orchestration (Docker, Kubernetes, EKS/AKS/GKE)

  • ML model deployment (real-time, batch, streaming)

  • Observability & monitoring (Prometheus, Grafana, CloudWatch, Datadog)

• Deep understanding of data pipelines, feature stores, and model registries .

• Ability to work independently as the lead architect in a client-facing environment.

• Excellent communication, stakeholder management, and presentation skills.

• Experience aligning architecture with Agile delivery methodologies .

• Cloud certifications (AWS Solutions Architect, Azure Architect, GCP Professional Cloud Architect).

• Certifications in ML engineering / MLOps (Databricks, TensorFlow, Google ML Engineer).

• Experience designing enterprise ML governance frameworks.

• Knowledge of security, data compliance, and responsible AI practices.

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