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Machine Learning Architect

1 month, 2 weeks ago
South Africa
Full-time
Lead
Machine Learning Engineer
Software Development
Apache Airflow Apache Spark AWS Azure CI/CD Databricks Feature Engineering GCP LLM Machine Learning MLOps Python SQL
Apply Now
Mindera

Mindera

Mindera is a global software engineering company that delivers high-performance web and mobile applications, empowering businesses with custom software solutions through Agile methodology and value-driven products.

Internet Software & Services
1K-5K
Founded 2014
$2M raised
View All Jobs 33

Description

  • Define and lead the architecture for scalable machine learning and AI platforms.
  • Design end-to-end machine learning workflows in Databricks, including feature engineering, model training, experimentation, deployment, and monitoring.
  • Architect scalable data pipelines for AI and ML workloads using Apache Spark, Python, and SQL.
  • Establish MLOps best practices, including CI/CD for machine learning, model versioning, governance, automated retraining, drift monitoring, and observability.
  • Design secure and compliant AI architectures aligned with governance and privacy standards.
  • Partner with Data Engineering teams to optimize data models and feature stores.
  • Guide Data Scientists and ML Engineers on scalable production design patterns.
  • Evaluate and integrate modern AI capabilities such as LLMs, vector databases, retrieval augmented generation, and AI agents as a plus.
  • Drive cost optimization, scalability, and operational excellence across ML platforms.
  • Define reference architectures and best practices across multiple ML teams and translate business needs into scalable technical solutions.

Requirements

  • 8+ years of experience in Data, AI, or Machine Learning Engineering roles.
  • 3+ years of experience designing ML platforms or AI architecture at scale.
  • Strong hands-on experience with Databricks, Apache Spark, Python, and SQL.
  • Strong understanding of MLOps and ML lifecycle management.
  • Experience with distributed ML systems, feature engineering, and model deployment patterns.
  • Experience with Databricks Unity Catalog, Delta Lake, and lakehouse architecture.
  • Experience with cloud platforms such as AWS, Azure, or GCP.
  • Experience deploying ML models into production environments.
  • Strong knowledge of data architecture and scalable ETL/ELT patterns.
  • Experience with orchestration frameworks such as Apache Airflow.
  • Strong stakeholder communication and technical leadership skills.

Interested in this position?

Apply directly on the company website

Apply Now

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