Job Purpose

Are you passionate about building enterprise-grade Machine Learning systems that drive real business impact? We are looking for a Senior Lead Machine Learning Engineer to lead the design, deployment, and operationalization of advanced ML solutions while mentoring teams and establishing MLOps best practices across the organization.

As a key member of the Group Analytics team, you will work closely with Data Scientists, Engineers, Architects, and Business stakeholders to deliver scalable, reliable, and production-ready AI solutions.

The Job

• Design, develop, and optimize machine learning models for enterprise use cases.
• Define model decision boundaries, validation processes, and hyperparameter tuning strategies.
• Build and maintain scalable ML/ Gen AI pipelines and serving infrastructure.
• Develop containerized model artifacts using Docker and Kubernetes.
• Implement advanced MLOps/ AIOps practices to support model lifecycle management.

• Design and maintain production-ready AI/ML deployment architectures.
• Establish CI/CD and version control best practices using platforms such as GitLab or CodeCommit.
• Develop and manage automated ML pipelines using cloud-native services.
• Monitor model performance, troubleshoot issues, and implement continuous improvements.
• Maintain monitoring, logging, and alerting mechanisms to ensure system reliability.

• Evaluate and implement emerging MLOps/ AIOps tools, frameworks, and technologies.
• Research optimization techniques to enhance model performance and efficiency.
• Drive continuous improvement initiatives and technology adoption across teams.
• Resolve complex technical challenges through experimentation and innovation.

• Lead and mentor ML engineering teams.
• Foster a culture of innovation, learning, and high performance.
• Collaborate with Data Scientists, Solution Architects, Cloud Operations teams, and business stakeholders.
• Build strong partnerships to deliver impactful AI-driven business outcomes.  

Qualifications & Experience

• Bachelor's Degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, Statistics, Software Engineering, Economics, Business, or a related field.
• Master's Degree is preferred Computer Science, Information Technology, Artificial Intelligence, Data Science, Statistics, Software Engineering, Economics, Business, or a related field.
• Professional DevOps certifications will be an added advantage.
• Cloud Solution Architect certification is preferred.

• 7 to 10 years of relevant industry experience in Machine Learning Engineering, Data Engineering, MLOps, or related disciplines.

• Proven experience designing and deploying enterprise-scale ML solutions.
• Strong programming experience in Python, Java/Spring Boot, JavaScript/Node.js, and related frameworks.
• Excellent SQL and database management knowledge.
• Experience with AWS services and cloud-native architectures.
• Strong understanding of Data Science, Analytics, Data Engineering, and ML system design.
• Experience with Docker, Kubernetes, CI/CD, model serving, monitoring, and automation.
• Familiarity with Agile and Scrum methodologies.
• Knowledge of telecom business operations will be advantageous.