Level

Mozn

AI Engineer

AI in this role

vertex-aiollamapytorchtensorflowmlflowsagemakerrunway
ml-ops

About Mozn

MOZN is a leading Enterprise AI company enabling organizations to make informed decisions in two critical domains: Financial Crime Prevention and Enterprise Knowledge Intelligence.

We’re a diverse, collaborative team of innovators united by a shared purpose: to build AI that delivers tangible business value, builds trust, and empowers people and organizations with augmented intelligence. Our culture is built on the relentless pursuit of excellence and meaningful impact.

If you’re passionate about working alongside exceptional talent on world-class AI, and you want the autonomy and runway to do the best work of your career, join us in shaping the future of intelligent enterprises.

About the role

We are looking for a AI Engineer to lead the design, deployment, and optimization of machine learning and generative AI solutions. The role focuses on applying advanced ML techniques to solve real-world challenges across government and enterprise clients in Saudi Arabia.

What you'll do

  • Designing, building, and scaling machine learning models and infrastructure
  • Deploying deep learning and generative models into production for public and private sector projects
  • Optimizing ML training and inference for performance, latency, and scalability
  • Monitoring, retraining, and improving deployed ML models
  • Driving consultation efforts, providing expert guidance to client stakeholders
  • Own the end-to-end delivery of AI solutions, including data pipelines, model development, backend services, APIs, integrations, user interfaces, deployment, and operations
  • Design and build data ingestion, transformation, and processing pipelines for structured and unstructured data
  • Develop backend services and APIs to expose AI capabilities securely and reliably
  • Build or contribute to frontend applications, dashboards, and interfaces for AI-powered solutions
  • Integrate AI solutions with enterprise systems, databases, authentication services, and third-party platforms

Requirements

  • Bachelor's or master's degree in computer science or related field
  • 3-5 years of experience across software engineering, ML engineering, data science, data engineering and generative AI.
  • Strong track record of projects across public and private sectors
  • Expertise in Python, TensorFlow, PyTorch, ONNX, and ML deployment frameworks
  • Expertise in containerization and orchestration technologies (Docker, Kubernetes), with hands-on experience in ML lifecycle management (MLflow) and local LLM deployment frameworks (Ollama)
  • Skilled in on-premise infrastructure design and enterprise architecture frameworks, with strong adherence to security and compliance best practices
  • Deep understanding of hardware provisioning for local LLM deployments (GPU, RAM, and storage optimization) and secure network configurations for internal AI services
  • Experience with cloud ML environments (SageMaker, Vertex AI, OCI Data Science)
  • Familiarity with MLOps practices and automation pipelines
  • Strong end-to-end engineering capabilities across AI, data engineering, backend development, APIs, integrations, and application deployment
  • Experience building data ingestion, transformation, and processing pipelines
  • Familiarity with backend frameworks such as FastAPI, Flask, Django, Node.js, or equivalent technologies
  • Experience designing and consuming REST APIs, webhooks, and enterprise integration interfaces
  • Working knowledge of frontend technologies such as React, Next.js, JavaScript, TypeScript, HTML, and CSS
  • Experience integrating AI solutions with databases, enterprise applications, identity and access management systems, and third-party services
  • Ability to independently build functional AI applications from prototype through production
  • Experience effectively using AI-assisted software development tools to accelerate prototyping and delivery

Benefits

  • You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space.
  • You will be given a lot of responsibility and trust. We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best.
  • The fundamentals will be taken care of: competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best
  • You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI.
  • We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves.

How we rate this

AI Engineer at Mozn rates 93 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

ML OpsVertex AIOllamaPyTorchTensorFlowMlflowSagemakerRunway

Questions you could be asked

  1. How do you monitor a model once it's live, and how do you know it needs retraining?
  2. Walk me through how you've used Vertex AI in your day-to-day work.
  3. What are the limits of Ollama that you've run into, and how did you work around them?
  4. What's a project where you used PyTorch hands-on?
  5. Walk me through how you've used TensorFlow in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: ML Ops, Vertex AI, Ollama, PyTorch, and TensorFlow. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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