AI Platform Engineer & Architect

Robotics Technologies LLC; Concord (CA); Presencial; USD 81.000 - 115.000; Jornada completa

Descripción de la vacante

Robotics Technologies LLC in Concord, CA seeks an AI Platform Engineer & Architect to design and implement high-availability model-serving systems for real-time inference, across Kubernetes-based platforms. The role involves building scalable deployment patterns and leading API-based inference service design.

You will collaborate with Data Science, Platform Engineering, MLOps and Infrastructure teams to ensure reliable production operations, establish monitoring and SLOs, and integrate inference

Formación

• Strong experience with online inference and production model-serving architectures.
• Hands-on Kubernetes, container orchestration, and service mesh experience.
• Proficiency in Python, Java, or Go.
• Experience with CI/CD, IaC, and cloud/on-prem platforms.

Responsabilidades

• Design and implement low-latency, high-availability model-serving architectures.
• Develop deployment patterns for scalable AI/ML services on Kubernetes.
• Lead API-based inference service design, deployment, and lifecycle management.
• Optimize performance via latency tuning, caching, autoscaling, and resource management.
• Establish monitoring, observability, SLOs/SLAs, alerts, and runbooks.
• Drive load testing, capacity planning, resiliency engineering, and disaster recovery readiness.
• Integrate inference platforms with CI/CD for automated releases.
• Collaborate with Data Science, Platform Eng, MLOps, and Infra teams.
• Define operational best practices, security standards, reliability measures.

Conocimientos

Kubernetes

Real-time inference

Distributed systems

API design

CI/CD / IaC

Performance tuning

Monitoring / Observability

Cloud & on-prem

Python / Java / Go

Herramientas

Docker

Istio / service mesh

CI/CD pipelines

IaC (Terraform)

Descripción del empleo

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.