Real-Time AI Platform Engineer & Architect

Machine Learning Technologies, LLC; Concord (CA); Sur place; USD 83 000 - 113 000; Plein temps

Résumé du poste

Machine Learning Technologies, LLC in Concord, CA is seeking an AI Platform Engineer & Architect to design and implement scalable model-serving architectures for real-time inference. You will drive deployment patterns across Kubernetes-based platforms and lead API-based inference service design and lifecycle management.

The role requires hands-on experience with Kubernetes, IaC, CI/CD, and observability to ensure reliable production AI deployments.

Qualifications

• Strong experience with online inference and production model-serving architectures.
• Experience with 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.

Responsabilités

• 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.

Connaissances

Real-time inference

Distributed systems design

Autoscaling & capacity planning

Performance engineering

Observability & tracing

CI/CD & IaC

Python/Go/Java

Cloud & on-prem integration

Frontend/backend integration

Outils

Kubernetes

Service Mesh

CI/CD pipelines

IaC (Terraform/CloudFormation)

Monitoring tools (Prometheus/Grafana)

GPU inference experience

Multi-cloud deployment

Description du poste

Machine Learning Technologies, LLC in Concord, CA is seeking an AI Platform Engineer & Architect to design and implement scalable model-serving architectures for real-time inference. You will drive deployment patterns across Kubernetes-based platforms and lead API-based inference service design and lifecycle management.

The role requires hands-on experience with Kubernetes, IaC, CI/CD, and observability to ensure reliable production AI deployments.