Remote ML Platform Architect

Quantiphi; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

Quantiphi is seeking a Technical Architect - ML with 8+ years in ML/AI engineering or MLOps to architect and implement enterprise-grade ML/LLM pipelines in a remote USA setting. You will lead design, governance, and automation across model lifecycles, leveraging SageMaker, Kubeflow, Airflow, and Bedrock.

Strong IAM/security focus and cross-functional collaboration are required. The role emphasizes cloud-native development, observability, and scalable deployment with CI/CD, Terraform/CDK, and

Qualifications

• 8+ years in ML/AI engineering or MLOps with architecture exposure.
• Strong expertise in AWS cloud-native ML stack, including SageMaker, EKS, Lambda, API Gateway, CI/CD.
• Hands-on with major MLOps toolsets: MLflow, Kubeflow, SageMaker Pipelines, Airflow, BentoML, KServe, Seldon.
• Deep understanding of model lifecycle management from feature engineering to deployment and monitoring.
• Experience with LLMops pipelines, prompt versioning and evaluation metrics.
• Strong ML lifecycle knowledge: data ingestion, feature engineering, training, evaluation, packaging, CI/CD, drift detection, monitoring, governance.
• AWS Bedrock and Agentcore exposure; CloudWatch, SageMaker Model Monitor, Prometheus/Grafana.
• Python proficiency and cloud-native patterns; security, IAM, secrets management, and artifact governance.

Responsibilities

• Architect and implement the MLOps strategy for the programme, aligned with project roadmap.
• Design and own enterprise-grade ML/LLM pipelines covering training, validation, deployment, versioning, monitoring and CI/CD.
• Build container-oriented ML platforms (EKS-first) while evaluating Kubeflow, SageMaker, MLflow, Airflow, etc.
• Implement hybrid MLOps + LLMOps workflows including prompt governance and evaluation frameworks.
• Serve as technical authority across internal and customer projects, sharing patterns and reusable frameworks.
• Enable observability, drift detection, lineage tracking and auditability across ML/LLM systems.
• Define standards for model deployment, monitoring, governance, and automation for reliability and scalability.
• Collaborate with data engineering, platform, DevOps and client stakeholders to deliver production ML solutions.
• Ensure security, governance and compliance for cloud services, Kubernetes workloads and MLOps tools.
• Mentor engineers on modern MLOps tools, platforms and best practices.

Skills

ML/AI engineering

MLOps

LLMOps

Python

Cloud-native dev

IAM security

Cross-team collaboration

Tools

SageMaker

Kubeflow

MLflow

Airflow

Seldon

BentoML

KServe

Terraform

Helm

CDK

Agentcore

Bedrock

CloudWatch

Prometheus

Grafana

Job description

Quantiphi is seeking a Technical Architect - ML with 8+ years in ML/AI engineering or MLOps to architect and implement enterprise-grade ML/LLM pipelines in a remote USA setting. You will lead design, governance, and automation across model lifecycles, leveraging SageMaker, Kubeflow, Airflow, and Bedrock.

Strong IAM/security focus and cross-functional collaboration are required. The role emphasizes cloud-native development, observability, and scalable deployment with CI/CD, Terraform/CDK, and