AI Platform Architect & Engineer - Real-Time Inference

Ethereum Technologies; Concord (CA); Presencial; USD 96.000 - 138.000; Jornada completa

Descripción de la vacante

Ethereum Technologies in Concord, CA seeks an AI Platform Engineer & Architect to design and operate production-grade model-serving systems for real-time inference at scale.

You'll lead Kubernetes-based deployments, APIs, and CI/CD integrations, collaborating with Data Science, Platform Eng, MLOps, and Infra teams to ensure reliability, performance, and security across enterprise AI workloads. Candidates must thrive in fast-paced environments and deliver measurable latency improvements.

Formación

• Experience designing production AI model-serving architectures.
• Strong knowledge of real-time APIs and distributed systems.
• Experience with Kubernetes-based platforms and CI/CD pipelines.

Responsabilidades

• Design high-availability, low-latency model-serving architectures for real-time inference workloads.
• Standardize deployment patterns for scalable AI/ML services on Kubernetes.
• Lead API-based inference service design, integration, deployment, and lifecycle management.
• Optimize performance with latency tuning, caching, autoscaling, and resource management.
• Establish monitoring, SLOs/SLAs, and runbooks for prod services.
• Drive load testing, capacity planning, resiliency engineering, and disaster recovery readiness.
• Integrate inference platforms with CI/CD pipelines to enable automated deployments and controlled releases.
• Collaborate with Data Science, Platform Eng, MLOps, and Infra teams to ensure reliability.

Conocimientos

Python

Go

Distributed systems

APIs

Herramientas

Kubernetes

CI/CD

Service Mesh

IaC (Terraform/CloudFormation)

Descripción del empleo

Ethereum Technologies in Concord, CA seeks an AI Platform Engineer & Architect to design and operate production-grade model-serving systems for real-time inference at scale.

You'll lead Kubernetes-based deployments, APIs, and CI/CD integrations, collaborating with Data Science, Platform Eng, MLOps, and Infra teams to ensure reliability, performance, and security across enterprise AI workloads. Candidates must thrive in fast-paced environments and deliver measurable latency improvements.