VP, Machine Learning.MGN Egypt
Egypt Full-time VP Machine Learning Engineering
At a glance
VP-level Machine Learning Engineering role at Mashreq Careers. Egypt · full-time.
Pay not stated Machine Learning Engineering salary
RoleMachine Learning Engineering
SeniorityVP
LocationEgypt
EmploymentFull-time
PostedJul 20, 2026 · 3mo ago
Role brief
aimlroles summary, based on the employer's posting.
What you'll do
- Lead the design and rollout of scalable machine learning systems, then improve them over time
- Set engineering practices for managing models throughout their lifecycle and monitoring them in production
- Build MLOps and CI/CD pipelines, including standards for model monitoring
- Work with data science, product and engineering teams to deliver machine learning solutions
- Grow the engineering team and guide its roadmap, architecture, hiring and delivery decisions
What you bring
- At least ten years in engineering, including leadership of machine learning work
- A track record of putting machine learning models into production at scale
- Hands-on knowledge of ML frameworks, cloud platforms and on-prem ML platforms
- Experience with MLOps, CI/CD and container tools such as Docker or Kubernetes
- Leadership, stakeholder communication and an understanding of ethical AI, privacy and compliance
Who this fits
This VP role suits a senior engineering leader who can set technical direction, build teams and make architecture and tooling decisions. You’ll work across data science, software engineering, product and business stakeholders in a cloud-native environment.
From the employer
Job Purpose
- Lead the development, deployment, and optimization of ML solutions across the organization
- Own and scale ML engineering teams and platforms
- Ensure alignment with business goals and technical excellence
- Drive innovation, efficiency, and enterprise ML adoption
Key Result Areas / Responsibilities
- Lead design, development, and deployment of scalable ML systems and platforms
- Drive ML engineering best practices, including lifecycle management
- Collaborate with Data Science, Product, and Engineering teams
- Establish MLOps, CI/CD pipelines, and model monitoring standards
- Mentor and grow ML engineering teams
Operating Environment
- Works in a cloud-native environment with modern ML frameworks
- Collaborates cross-functionally with:
- Data Scientists
- Software Engineers
- Product Managers
- Business stakeholders
Decision Authority
- Own ML engineering roadmap and technology stack
- Responsible for:
- Hiring and team structure
- Architecture decisions
- Delivery quality and timelines
- Decide on vendor and tooling strategy
Skills & Experience
- 10+ years engineering experience, including ML leadership
- Proven experience deploying ML models at scale in production
- Expertise in:
- ML frameworks
- On-prem ML platform and Cloud platforms (Azure/AWS/GCP)
- MLOps, CI/CD, containerization (Docker, Kubernetes)
- Strong leadership, stakeholder management, and communication skills
- Understanding of ethical AI, privacy, and compliance
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