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Machine Learning Engineer

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Dotdigital

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Location:
South Africa

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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Job Description:

We’re looking for a highly skilled Machine Learning Engineer to join our data and analytics team. You’ll design, build, and optimize scalable, high-performance data pipelines and ML workflows on Databricks, leveraging PySpark, Unity Catalog, and modern data lake house technologies such as Delta Lake and Apache Iceberg. This is an exciting opportunity to shape our ML infrastructure and production pipelines, working at the intersection of data engineering and applied machine learning. We supply our customers with an array of predictive data science models. We do this for all of our customers meaning we train and execute 1000’s of models that are uniquely configured to provide tailored results.

Job Responsibility:

  • Architect and implement high-throughput data pipelines using PySpark on the Databricks platform to support large-scale ML workloads
  • Develop and operationalise ML workflows and model pipelines leveraging industry-leading frameworks and MLOps practices
  • Drive data governance and metadata management via feature stores to ensure data quality, lineage and compliance
  • Work with modern data lake house storage formats such as Delta Lake and Apache Iceberg to deliver reliable, performant data architectures
  • Collaborate across cross-functional teams including data engineering, data science, analytics and product to translate business challenges into scalable ML solutions
  • Monitor, tune and optimise the performance, cost-efficiency and reliability of data/ML pipelines in a production environment
  • Stay abreast of emerging technologies and best practices in data engineering, ML infrastructure and pipeline design to lift our platform continuously

Requirements:

  • A strong track record (typically 5+ years) in data engineering or ML engineering, with significant experience in building large-scale data pipelines and production ML systems
  • Proficiency in Python, and strong hands-on experience with PySpark in distributed, big-data environments
  • Proven experience with Databricks (cluster config, job orchestration, runtime optimisation)
  • Deep understanding and practical use of Unity Catalog, Delta Lake and Apache Iceberg in data lake house architectures
  • Expertise in data modelling, partitioning strategies, performance tuning and best practices for high-throughput data systems
  • Familiarity with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and experience deploying models into production
  • Experience with CI/CD pipelines for data and ML code
  • Excellent communication skills and ability to work collaboratively in agile team environments
  • Proven experience owning complex technical problems, guiding and influencing cross-team solutions and lifting platform standards
  • Comfortable driving infrastructure or platform-level initiatives, making architectural decisions that align with business outcomes
  • A proactive mindset with the ability to identify and evangelise tools, practices and improvements that elevate the team’s capability

Nice to have:

  • Experience on cloud platforms such as AWS, Azure or GCP
  • Exposure to streaming architectures (e.g., Structured Streaming, Kafka) or real-time ML
  • Background with feature stores, data governance frameworks or data quality tooling
  • Experience using Databricks or similar data platforms
What we offer:
  • Parental leave
  • Medical benefits
  • Paid sick leave
  • Dotdigital day
  • Share reward
  • Wellbeing reward
  • Wellbeing Days
  • Loyalty reward

Additional Information:

Job Posted:
December 08, 2025

Employment Type:
Fulltime
Work Type:
Remote work
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