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The number 1 Top Employer in South Africa. 
Certified by the Top Employer Institute 2025.
 

Role Purpose/Business Unit:

 

The Machine Learning Engineer (MLE) will report to the Group AI/ML Tech Lead within Vodacom Group Technology. This role is critical in enabling and operationalizing AI systems and Machine Learning (ML) models developed by the Data Science team. The MLE will own the enabling technology for the ML platform and AI systems for specific applications or products. The primary responsibility is to design, build, and optimize AI systems while contributing to the evolution of the ML platform to streamline model development and MLOps processes.

Additionally, the MLE will collaborate with Data Scientists to transfer knowledge, improve usability, and enhance existing AI systems. The role also requires system design, architectural enhancements, and the creation of Standard Operating Procedures (SOPs) to ensure scalability, reliability, and operational efficiency of AI solutions.

Your responsibilities will include:

 

Strong systems-thinking mindset to design end-to-end ML solutions.Ability to research and prototype novel solutions for unstructured or ambiguous problems.Proactive self-leadership with the ability to drive initiatives independently.A clear communicator who can translate complex technical ideas into business-aligned solutions.Collaborative mindset, working effectively across teams to bridge gaps between business, Data Science, and Engineering.A continuous learner, with a keen interest in emerging ML technologies and software engineering trends.Able to balance long-term vision and immediate project goals with a focus on delivering business value.The ideal candidate for this role will have:

 

3+ years of Machine Learning Engineering experience (hands-on).Strong understanding of Machine Learning algorithms and their foundational principles.3+ years of experience deploying and operationalizing ML models, including CI/CD pipelines for models.Software Engineering experience (strongly preferred):Designing and implementing APIs for model serving.Building scalable, production-grade microservices to support AI/ML systems.Strong understanding of software development lifecycle (SDLC) and best practices.Proven ability to bridge gaps between Data Science and Software Engineering teams.Worked in an Agile environment, collaborating with cross-functional teams.Minimum of 5 years of Python development experience (must include ML and software development applications).Familiarity with cloud platforms (AWS, GCP, Azure) and tools for deploying AI systems.1+ year of experience with Kubernetes/Docker for containerized model deployment is advantageous.Systems engineering experience or exposure is beneficial.A Bachelor's degree in STEM is required; a Master's degree or Ph.D. is highly advantageous.

 

 

Technical Competencies:

 

1.    Core Competencies:

Proficiency in Python for building ML models and software systems.Strong experience with Git and CI/CD pipelines for model and software deployment.Knowledge of MLOps frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI) to operationalize and monitor ML models.Design and optimization of scalable ML systems, including feature engineering pipelines and real-time model inference.Knowledge of database systems (SQL and NoSQL) for data storage and feature serving.Solid understanding of containerization and orchestration tools like Docker and Kubernetes.

2.    Cloud and Platform Expertise:

Experience working with cloud-native services for ML (e.g., AWS SageMaker, GCP Vertex AI, Azure ML).Understanding of distributed computing frameworks (e.g., Apache Spark, Dask) to handle large-scale data processing.

3.    Systems and Integration:

Experience in integrating ML models into APIs and production systems.Strong understanding of system reliability, monitoring, and logging for production-grade AI systems.

4.    Advanced Skills:

Knowledge of Feature Store platforms (e.g., Feast, Tecton) for operationalizing feature engineering.Hands-on experience with model monitoring and retraining pipelines to manage model drift and decay.Exposure to scalable message brokers (e.g., Kafka, RabbitMQ) for real-time data streaming.We make an impact by offering:

 

Enticing incentive programs and competitive benefit packagesRetirement funds, risk benefits, and medical aid benefitsCell phone and data benefits, advantages fibre connection discounts, and exclusive staff discounts offered in collaboration with partner companies

 

Closing date for Applications: 14 February 2025. 

The base location for this role is Midrand, Vodacom Campus. 

The company's approved Employment Equity Plan and Targets will be considered as part of the recruitment process. As an Equal Opportunities employer, we actively encourage and welcome people with various disabilities to apply.
Vodacom is committed to an organisational culture that recognises, appreciates, and values diversity & inclusion.