View

Ethereum Technologies; Concord (CA); On-site; USD 96,000 - 138,000; Full time

Job summary

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.

Qualifications

• 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.

Responsibilities

• 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.

Skills

Python

Go

Distributed systems

APIs

Tools

Kubernetes

CI/CD

Service Mesh

IaC (Terraform/CloudFormation)

Job description

Job Title: AI Platform Engineer & Architect
Location: Concord, CA
Duration: 12 Months + Extension
Bill Rate: $71/hour
Job Type: W-2 Contract
Client: To Be Discussed Later
Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD

Key Responsibilities

• Design and implement highly available, low-latency model-serving architectures for real-time inference workloads.
• Develop and standardize deployment patterns for scalable AI/ML services across Kubernetes-based platforms.
• Lead API-based inference service design, integration, deployment, and lifecycle management.
• Optimize model-serving performance through latency tuning, caching strategies, autoscaling, and resource management.
• Establish monitoring, observability, SLOs/SLAs, alerting, and operational runbooks for production 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 Engineering, MLOps, and Infrastructure teams to ensure reliable production model operations.
• Establish operational best practices, security standards, reliability measures, and performance benchmarks for enterprise AI deployments.

Required Technical Skills

• Strong experience with online inference and production model-serving architectures.
• Expertise in real-time APIs and distributed systems design.
• Hands-on experience with Kubernetes, container orchestration, and service mesh technologies.
• Knowledge of autoscaling, capacity management, and workload optimization.
• Experience in performance engineering, load testing, and latency optimization.
• Strong understanding of monitoring, observability, logging, distributed tracing, and SLO management.
• Experience with CI/CD, DevOps, and Infrastructure as Code (IaC).
• Knowledge of reliability engineering, fault tolerance, and resiliency patterns.
• Experience operating cloud-based and on-premises platforms.
• Proficiency in Python, Java, Go, or similar backend programming languages.

Preferred Qualifications

• Experience with MLOps platforms and enterprise AI deployment frameworks.
• Hands-on experience with real-time recommendation, fraud detection, risk assessment, personalization, or predictive analytics platforms.
• Familiarity with GPU-based inference, model optimization, and multi-cloud deployments.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.