Senior Lead Machine Learning Engineer

About the role

Talent Express is recruiting a Senior Lead Machine Learning Engineer who designs, develops, optimizes and deploys machine learning models for enterprise use cases, and leads the machine learning engineering teams. The role covers model architecture, MLOps/AIOps, cloud infrastructure and mentoring engineers.

Key responsibilities

• Design, develop, optimize and deploy machine learning models for enterprise use cases, defining decision boundaries, validation methods and hyperparameter tuning strategies.
• Architect and maintain scalable ML/Gen AI pipelines and model-serving infrastructure, including containerized artifacts with Docker and Kubernetes.
• Implement MLOps/AIOps practices and production-ready AI/ML deployment architectures.
• Set up CI/CD, version control and DevOps best practices on platforms such as GitLab and CodeCommit, and build automated ML pipelines with cloud-native services.
• Monitor model performance, troubleshoot production issues and set up monitoring, logging and alerting.
• Evaluate emerging MLOps, AIOps and AI/ML tools, research optimization techniques, and drive continuous improvement across teams.
• Lead, mentor and develop machine learning engineering teams, collaborating with data scientists, solution architects, cloud operations teams and business stakeholders.

Required profile

• Bachelor's degree in Computer Science, IT, AI, Data Science, Statistics, Software Engineering, Economics, Business or a related field; a Master's degree is an added advantage.
• 5 years of industry experience in Machine Learning Engineering, Data Engineering, MLOps or related fields, with proven experience designing and deploying enterprise-scale ML/AI solutions.
• Familiarity with Agile and Scrum; professional DevOps certifications are an added advantage, and a Cloud Solution Architect certification is preferred.
• Knowledge or experience in the telecommunications industry is an added advantage.

Required skills

• Strong programming in Python, Java/Spring Boot, JavaScript/Node.js and related frameworks.
• Excellent SQL and database management knowledge.
• Hands-on experience with AWS, Docker, Kubernetes, CI/CD, model serving, monitoring and automation.
• Understanding of MLOps/AIOps and ML system design.
• Leadership, communication, problem-solving and stakeholder management skills.