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AI/ML Platform Engineer (Kubernetes & MLOps)

Jobs for Humanity · Riyadh, Riyadh Region, Saudi Arabia · SAR 180K/yr

Non-profit Organizations · 11-50 employees

6 h ago
Mid (2-5 yrs) Full-time Saudi Arabia
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About the role

You will own the deployment and operational excellence of AI/ML services by establishing robust CI/CD, model serving, and lifecycle management on Kubernetes. The role focuses on optimizing inference performance and ensuring reliable releases while reducing infrastructure costs.

What they look for

Kubernetes Docker Python MLOps CI/CD GitHub Actions Jenkins TensorFlow PyTorch MLflow Prometheus Grafana Kafka RabbitMQ REST gRPC

Requirements

The ideal candidate must have production experience in MLOps and AI, with strong proficiency in Kubernetes, Docker, and Python. You are expected to be skilled in model serving, monitoring tools, and automated pipeline development.

Full description

Company Description

Jobs for Humanity is partnering with Kanz 30 to build an inclusive and just employment ecosystem. Therefore, we prioritize individuals coming from all walks of life.

Company Name: Kanz 30

Job Description

We are seeking an MLOps/AI Platform Engineer to build, deploy, and scale production AI/ML services on Kubernetes. You will partner with ML engineers and software teams to operationalize models with strong reliability, performance, and cost efficiency using automated pipelines, monitoring, and end-to-end MLOps practices.

Job Purpose Own the deployment and operational excellence of AI/ML services by establishing robust CI/CD, model serving, observability, and lifecycle management on Kubernetes—optimizing inference performance (latency/throughput), ensuring reliable releases, and reducing infrastructure and operating costs.

Job Duties and Responsibilities

  • Kubernetes
  • Docker
  • CI/CD (GitHub Actions/Jenkins)
  • Python
  • REST/gRPC model serving
  • MLflow
  • TensorFlow or PyTorch
  • Prometheus/Grafana
  • Kafka/RabbitMQ
  • Monitoring and alerting
  • Automated MLOps practices
  • Model performance optimization
  • Cost optimization

Qualifications

Required Qualifications

  • Kubernetes
  • Docker
  • Python
  • MLflow
  • TensorFlow or PyTorch
  • REST/gRPC model serving
  • CI/CD (GitHub Actions/Jenkins)
  • Prometheus/Grafana
  • Kafka/RabbitMQ
  • AWS/GCP/Azure basics
  • Monitoring and incident response
  • MLOps/production AI experience
  • Company: Kanz 30
  • Compensation: SAR 0 - SAR 15000 - monthly