Senior MLOps Engineer: Build Self-Serve AI Platform

Fathom.io; Dhahran Compound; On-site; SAR 260,000 - 420,000; Full time

Job summary

Fathom.io is seeking a mid-to-senior MLOps engineer to build the intelligence layer of our AI platform in Dhahran, Saudi Arabia. You will design infrastructure for model deployment, training, notebooks, UI-driven agents, and RAG pipelines, enabling self-service workflows across GPU and edge deployments.

You’ll work at the intersection of platform engineering, ML infrastructure, distributed systems, and developer experience, collaborating with backend and AI teams to deliver reliable, scalable

Qualifications

• Strong experience in MLOps, AI platform engineering, machine learning infrastructure, or distributed systems.
• Hands-on Kubernetes experience, including deploying and operating stateful, training, notebooks, serverless, or GPU-intensive workloads.
• Experience building ML platforms that support training, experimentation, notebooks, feature/data workflows, model registries, and production serving.
• Experience with model serving frameworks such as KServe, vLLM, Triton, Ray Serve, or similar.
• Familiarity with ML lifecycle tooling such as MLflow, experiment tracking, model registries, and CI/CD or GitOps for ML systems.
• Practical experience optimizing training and inference workloads for latency, throughput, availability, and cost.
• Understanding of GPU scheduling, resource allocation, model quantization, batching, autoscaling, and multi-model serving.
• Experience with RAG systems, LLM applications, AI agents, or their supporting infrastructure.
• Strong software engineering fundamentals and a product-minded approach to platform design.
• Ability to make complex operational workflows reliable and approachable for users.

Responsibilities

• Design and build the infrastructure powering our Intelligence layer.
• Enable reliable, automated workflows for model training, deployment, lifecycle management, and inference.
• Build scalable foundations for users to create, configure, and operate AI agents and RAG pipelines through the platform UI.
• Develop the platform capabilities behind managed notebooks, functions, experiments, training jobs, model registries, and serving endpoints.
• Improve model serving, observability, versioning, evaluation, promotion, and rollback capabilities.
• Optimize GPU inference and training deployments for performance, reliability, and cost efficiency.
• Explore efficient approaches for deploying models across centralized GPU infrastructure and edge devices.
• Automate workflows that otherwise require manual MLOps effort, with a focus on safe, self-service capabilities for platform users.
• Partner with backend, product, and AI teams to turn complex infrastructure into intuitive platform features.
• Help define standards for security, multi-tenancy, resource isolation, model governance, and operational reliability.

Skills

MLOps

Distributed systems

Platform engineering

Rust (advantage)

Kubernetes

KServe

Tools

Kubernetes

Knative

MLflow

LangFuse

GPU infrastructure

Job description

Fathom.io is seeking a mid-to-senior MLOps engineer to build the intelligence layer of our AI platform in Dhahran, Saudi Arabia. You will design infrastructure for model deployment, training, notebooks, UI-driven agents, and RAG pipelines, enabling self-service workflows across GPU and edge deployments.

You’ll work at the intersection of platform engineering, ML infrastructure, distributed systems, and developer experience, collaborating with backend and AI teams to deliver reliable, scalable