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