MLOps Engineer

Salt Digital Recruitment; Abu Dhabi; On-site; AED 180,000 - 240,000; Full time

Job summary

Salt Digital Recruitment is seeking to join a brand-new project in an Innovation Hub/AI Lab to design and develop a ML platform that empowers the Data Science and AI team to scale experimentation and speed up path to production.

The role focuses on CI/CD/CT pipelines, model serving architectures for ultra-low latency real-time APIs and large-scale batch inference, and on monitoring, governance, and auditable lineage of ML artifacts using MLflow and Kubeflow.

Qualifications

• 3-7 years of experience building and operating high-availability ML pipelines and infrastructure.
• Strong programming skills in Python, Go or Java and Linux scripting.
• Hands-on experience with MLflow, Kubeflow or Argo workflows and model registry tooling.
• Experience with cloud security, IAM, VPC isolation and encryption at rest/in transit.

Responsibilities

• Design and automate robust ML pipelines for CI/CD/CT of models.
• Configure model serving architectures for real-time and batch inference.
• Implement monitoring, logging and data drift detection in production.
• Manage model registries and reproducible artifact lineage (MLflow/Kubeflow).
• Scale containerized apps with Docker and Kubernetes or managed services.
• Collaborate with security and data teams on data governance and encryption policies.

Skills

Python

Go

Java

Linux

CI/CD

MLOps

Security

Tools

MLflow

Kubeflow

Argo Workflows

Feast

SageMaker

Azure ML

Docker

Kubernetes

Terraform

CloudFormation

Job description

We are working on a brand-new project, which is an Innovation Hub/Ai Lab.

Job Purpose

Designs and develops a ML platform to empower the Data Science and AI team to scale ML experimentation and speed up path to production.

Key Responsibilities

• Design and automate robust ML pipelines for continuous integration, continuous delivery, and continuous training (CI/CD/CT) of models.
• Configure model serving architectures to support both ultra-low latency real-time APIs (e.g., FastAPI, gRPC) and large-scale batch inference.
• Implement model monitoring and logging systems to track model metrics, runtime latencies, data drift, and concept decay in production.
• Manage model registries and metadata to ensure reproducible versioning, tracking, and auditable lineage of ML artifacts (using MLflow, Kubeflow, etc.).
• Orchestrate and scale containerized applications using Docker and production-grade Kubernetes or managed container services (EKS, AKS).
• Collaborate with security and data teams to enforce strict data governance, pipeline encryption, network isolation, and secure IAM policies.

Qualifications/Experience

• 3-7) years of experience building and operating high-availability ML pipelines, automation scripts, and foundational platform infrastructure layers.
• Strong programming skills in Python, Go, or Java alongside systems scripting and deep hands-on familiarity with Linux environments.
• Deep familiarity with MLOps tools such as MLflow, Kubeflow, Argo Workflows, Feast, or managed platform equivalents (SageMaker, Azure ML).
• Understanding of cloud security architectures including VPC isolation, private endpoints, encryption at rest/in transit, and role-based access control.
• Understanding of containerization and orchestration using Docker and Kubernetes, alongside Infrastructure-as-Code (Terraform, CloudFormation).

Salt is acting as an Employment Business in relation to this vacancy.