M
Mashreq
ML Engineer
VP, Machine Learning.MGN Egypt
On-siteStaffML Engineerposted 3mo ago
Role summaryAI-generated
This VP-level role demands a seasoned leader to architect and scale ML systems while mentoring engineering teams, ensuring seamless integration with business objectives in a cloud-native environment. The ideal candidate will drive innovation through MLOps standardization and foster collaboration across data science, product, and engineering disciplines.
Skills required
Scalable ml pipelinesMlops ci cdModel monitoringCloud native architecturesTeam leadershipMl engineering best practicesCross functional collaborationEnterprise ml scalingData lifecycle managementTechnical excellenceMachine learningData scienceMLOpsCI/CDCloud computingAzureAWSGCPDockerKubernetesStakeholder managementAI
About this role
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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