MLOps Platform Engineer - Build AI Workflows

Fathom.io; Saudi Arabia; On-site; SAR 240,000 - 480,000; Full time

Job summary

Fathom.io is seeking a mid-to-senior MLOps engineer to help build the intelligence layer of our AI platform. You will design infrastructure for model deployment, training, notebooks, functions, and RAG pipelines, enabling self-service workflows.

You will work at the intersection of platform engineering, ML infrastructure, distributed systems, and developer experience, delivering scalable, secure solutions for GPU-heavy workloads and edge deployments.

Qualifications

• Must have strong experience in MLOps, AI platform engineering, ML infrastructure, or distributed systems.
• Hands-on Kubernetes experience with stateful, training, notebook, serverless, or GPU workloads.
• Experience building ML platforms supporting training, experiments, notebooks, feature/data workflows, model registries, and production serving.
• Familiarity with model serving frameworks such as KServe, vLLM, Triton, or Ray Serve.
• Experience with ML lifecycle tooling, experiment tracking, model registries, and CI/CD or GitOps for ML systems.
• Experience optimizing training and inference workloads for latency, throughput, and cost.
• Understanding of GPU scheduling, quantization, batching, autoscaling, and multi-model serving.

Responsibilities

• Design and build the infrastructure powering our Intelligence layer.
• Enable automated workflows for training, deployment, lifecycle management, and inference.
• Build scalable foundations for users to create AI agents and RAG pipelines through the platform UI.
• Develop capabilities for notebooks, functions, experiments, training jobs, and model registries.
• Improve model serving, observability, versioning, evaluation, promotion, and rollback capabilities.
• Optimize GPU inference and training deployments for performance and cost.
• Explore deployment of models across centralized GPUs and edge devices.
• Automate workflows to reduce manual MLOps effort with safe, self-service features.
• Collaborate with backend, product, and AI teams to turn infrastructure into platform features.
• Help define security, multi-tenancy, resource isolation, and model governance standards.

Skills

MLOps

AI platform engineering

Distributed systems

Kubernetes

Platform design

Product-minded

Self-service UX

Tools

Kubernetes

Knative

KServe

vLLM

MLflow

LangFuse

Job description

Fathom.io is seeking a mid-to-senior MLOps engineer to help build the intelligence layer of our AI platform. You will design infrastructure for model deployment, training, notebooks, functions, and RAG pipelines, enabling self-service workflows.

You will work at the intersection of platform engineering, ML infrastructure, distributed systems, and developer experience, delivering scalable, secure solutions for GPU-heavy workloads and edge deployments.