drjobs Senior ML Engineer

Senior ML Engineer

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1 Vacancy
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Job Location drjobs

Cape Town - South Africa

Monthly Salary drjobs

Not Disclosed

drjobs

Salary Not Disclosed

Vacancy

1 Vacancy

Job Description

Senior ML Engineer 12 Month Contract

Key Responsibilities
  • Design develop and deploy ML models in AWS SageMaker and EKS.

  • Optimize ML models for realtime decisioning in hightraffic environments.

  • Ensure models comply with regulatory and security standards.

  • Build and maintain CI/CD pipelines for ML model deployments.

  • Automate model retraining monitoring and logging using AWS Lambda Terraform and ControlM jobs.

  • Implement observability tools like OpenSearch FluentBit Prometheus Kibana Grafana and AWS CloudWatch.

  • Develop ETL/ELT pipelines for data preprocessing and feature engineering.

  • Work with AWS Redshift to process largescale datasets for model training.

  • Monitor ML models running 24/7 in production ensuring reliability and high availability.

  • Work closely with engineering teams to troubleshoot and optimize production systems.

  • Participate in an oncall rotation for urgent ML pipeline issues.

  • Collaborate with data scientists decision engineers and credit engineers to align ML solutions with business needs.

  • Take ownership of ML solutions and provide guidance to junior engineers.

  • Contribute to the ongoing AI/ML strategy within the business.

Required Skills & Qualifications:
Technical Skills:
  • 5 years of experience in Machine Learning Engineering.

  • Strong expertise in Python PySpark SQL and ML libraries (TensorFlow PyTorch Scikitlearn).

  • Experience with AWS ML services (Amazon SageMaker EKS Lambda Redshift ControlM Terraform).

  • Experience with MLOps practices (CI/CD pipelines with GitHub Actions Docker Kubernetes).

  • Proficiency in observability & monitoring tools: OpenSearch FluentBit Kibana Prometheus Grafana CloudWatch.

  • Strong understanding of realtime ML applications in financial environments.

  • Experience in building and maintaining ETL pipelines in a cloud environment.

Soft Skills:
  • Leadership & Ownership Ability to work independently and drive ML initiatives.

  • ProblemSolving Ability to troubleshoot ML model failures in production.

  • Strong Communication Work effectively with crossfunctional teams.

  • Agility Adapt to a fastpaced highstakes environment.

  • Banking Industry Experience Preferred.


Employment Type

Full Time

Company Industry

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