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Senior Machine Learning Engineer
Absa GroupSenior Machine Learning Engineer at Absa responsible for designing and deploying ML solutions. Collaborating with various stakeholders to ensure production-ready models with measurable business value.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing, building, and deploying machine learning models while implementing MLOps practices for performance monitoring and maintenance. Strong background in data governance and collaboration with cross-functional teams to align with enterprise standards.
Highest-signal resume keywords
Machine Learning Model DevelopmentMLOps PracticesPython ProgrammingData Pipeline EngineeringCloud ML/Engineering Certifications
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningData SciencePythonSQLMLOps ToolingModel ExplainabilityData Quality ChecksAPI Deployment PatternsProduction ML FrameworksStatistical Analysis
Soft Skills
CollaborationCommunicationTeam Management
Tools & Technologies
Scikit-learnPyTorchTensorFlowAzureAWSGCP
Certifications & Qualifications
Cloud ML/EngineeringData EngineeringSecurityResponsible AI
Industry Keywords
Data GovernanceEnterprise StandardsEmerging TechnologiesBest Practices in ML EngineeringModel Monitoring
Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud PlatformPythonPyTorchScikit-LearnSQLTensorflow
About the role
Key responsibilities & impact- Design, build, and deploy machine learning models
- Collaborate closely with the Manager: New Tech and AI
- Implement MLOps practices to monitor and maintain performance
- Support data governance initiatives
- Collaborate with cross-functional teams and align to enterprise standards
- Stay informed about emerging technologies and best practices in ML engineering
Requirements
What you’ll need- 7 + years experience
- Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related field
- Postgraduate qualification (advantageous) in Machine Learning, Data Science, AI, or Software Engineering
- Relevant certifications (advantageous): Cloud ML/Engineering (e.g., Azure/AWS/GCP), data engineering, security, or Responsible AI
- 4 years in a technical position or team management
- Python and production ML frameworks (e.g., scikit-learn, PyTorch/TensorFlow)
- MLOps tooling and patterns (CI/CD for ML, model registries, experiment tracking, model monitoring)
- Data pipeline engineering (SQL, orchestration concepts, distributed processing concepts, data quality checks)
- API/service deployment patterns (containerisation concepts, service integration, authentication/authorisation)
- Model explainability, fairness testing, robustness checks, and governance documentation practices
- Secure engineering practices aligned to enterprise standards
Benefits
Comp & perks- Health insurance
- Paid time off
- Professional development opportunities