Salary
≈ $44k – $106k per year (Estimated)
Location
In office (Sri Lanka)
Seniority
Staff
Confirmed on the employer's own hiring board on Oct 19, 2026. First seen by Alion on Oct 18, 2026.
Overview
Company
Impact
Profile match
Dialog Axiata is the largest mobile network operator in Sri Lanka. Its services cover mobile, fixed broadband, television and digital finance. The company operates within a regional telecommunications group.
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.
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