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Vodafone • Johannesburg, South Africa

Senior Specialist Machine Learning

Employment type:  Full time
8.4

/10

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Job Description

When it comes to putting people first, we're number 1.

The number 1 Top Employer in South Africa.
Certified by the Top Employer Institute 2026.

Role Purpose/Business Unit:

As a Senior Machine Learning Engineer, you will play a critical role in designing, deploying, and operationalizing scalable machine learning solutions across multiple markets. You will work with cross-functional teams, including data scientists, data engineers, software engineers, and product managers to integrate models into production with a robust MLOps lifecycle. This role demands strong experience in ML engineering at scale, advanced automation, real-time model serving, and compliance-aware development.

Your responsibilities will include:

  • ML System Design & Architecture: Architect and implement scalable, secure ML pipelines using tools like MLflow, SageMaker, or Databricks. Design reusable templates for batch and real-time inference.
  • Production Model Deployment: Automate deployment of models into production with CI/CD, containerization (Docker), orchestration (Kubernetes), and feature stores.
  • Model Monitoring & Governance: Implement real-time model monitoring, drift detection, and lineage tracking to ensure model performance and compliance.
  • Collaboration & Delivery: Partner with data scientists to translate prototypes into production-ready code. Engage with software and data engineering teams to integrate models into larger systems and APIs.
  • Automation & Testing: Enforce test-driven development for model code. Implement automated tests for pipelines, accuracy thresholds, and data validation.
  • Documentation & Knowledge Sharing: Maintain clear technical documentation for models, pipelines, and workflows. Lead internal workshops on MLOps best practices and tooling.
  • Mentorship: Mentor junior MLEs and data scientists on engineering best practices, reproducibility, and scalable ML system design.

The ideal candidate for this role will have:

Education:

  • Bachelor’s degree in Computer Science, Data Science, Engineering, Applied Mathematics, or a related field.
  • Master’s degree or PhD preferred (especially with specialization in Machine Learning, AI, or Distributed Systems).

Experience:

  • 8+ years in data science or ML engineering roles, including at least 5 years in production-grade ML deployment and operationalization.
  • Hands-on experience with distributed computing frameworks and model orchestration at enterprise scale.

Preferred Certifications

  • AWS Certified Machine Learning – Specialty
  • Databricks Certified ML Professional
  • Kubernetes Administrator (CKA)
  • MLflow or MLOps specialization (e.g., DeepLearning.AI, Coursera)

Core competencies, knowledge, and experience:

Technical Skills

  • Languages: Python (mandatory), Bash, SQL; optional: Scala or Java.
  • ML Libraries & Frameworks: Scikit-learn, XGBoost, TensorFlow, PyTorch.
  • MLOps & Model Lifecycle: MLflow, SageMaker, Databricks, Kubeflow, Airflow.
  • Infrastructure: AWS (EC2, S3, SageMaker, IAM, EKS), Terraform, Kubernetes, Docker.
  • Feature Engineering: Feature Stores (e.g., SageMaker Feature Store, Feast).
  • Monitoring: Prometheus, Grafana, CloudWatch, Evidently AI.
  • Security & Compliance: RBAC, KMS, encryption, reproducibility, model versioning.

Soft Skills

  • Strategic problem-solver with strong system thinking.
  • Excellent communication and technical storytelling across technical and business stakeholders.
  • Comfortable working in agile squads and fast-paced delivery environments.
  • Passionate about enabling ML at scale and setting engineering standards.

We make an impact by offering:

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


Closing date for Applications: 06 April 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.

Company benefits

UK (28), India (22), Egypt (21), Hungary (20), Romania (20), Albania (22), Turkey (14) days annual leave + bank holidays
Work from anywhere scheme – work for up to 20 days/year abroad (dependant on country)
Annual bonus – dependant on company performance
Employee discounts
Personal development days – once per quarter
Learning platform – access to Harvard Business Publishing, MIT Horizon and Skillsoft
Enhanced maternity leave – 16 weeks (paid) with a phased return to work over 6 months
Enhanced paternity leave – 16 weeks (paid) with a phased return to work over 6 months
Volunteer days – up to 5 days
Coaching – access to a free certified internal pool of coaches
Mentoring
Carer’s leave
Adoption leave – 16 weeks (paid) with a phased return to work over 6 months
Enhanced sick days
Mental health platform access
Mental health first aiders
Employee assistance programme
Complimentary Medical Services – 24/7 online doctor service
Compassionate leave
Home office set up
Buddy scheme
Referral bonus
Early finish Fridays
Buy or sell annual leave
Cycle to work scheme
Life insurance
Sabbaticals
Salary sacrifice
Share options
Teambuilding days
Faith rooms
Enhanced pension match/contribution
Learning license

Working at Vodafone

Company employees:

85,887

Gender diversity (m:f):

61:39

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