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Machine Learning Operations Engineer

2 months ago

Cape Town, Western Cape, South Africa Flash Full time
Flash Cape Town CBD

Job Ref #: FH-198

Industry: Fintech

Job Type: Permanent

Positions Available: 1

We are seeking a highly skilled Machine Learning Operations Engineer to lead the development and execution of our ML Ops strategy.

The ideal candidate will have significant experience in working with various technologies related to Data Ops, ML Ops, and AI, as well as strong analytical and problem-solving skills.

Key Responsibilities:
  1. Contribute to the development of our Data Science and AI strategy, focusing on operationalizing machine learning models.
  2. Design and build automated, scalable, and reliable Machine Learning CI/CD pipelines, including automatic re-training, re-testing, and re-deploying.
  3. Manage and monitor productionized machine learning models.
  4. Enhance data collection procedures to include relevant information for building analytic systems.
  5. Assist in the integration and development of an external analytics system, involving various data processing and data science technologies.
  6. Enable smarter processes and implement analytics for meaningful insights.
  7. Stay up-to-date with technical and industry developments.
  8. Communicate findings to all stakeholders.
Requirements:
  1. B. Sc or B. Com in Physics, Computer Science, Applied Mathematics, Statistics, Data Science, Software Engineering, or similar.
  2. 5+ years of relevant professional experience, preferably in the fintech industry.
Desirable Skills:
  • Strong analytical and problem-solving skills.
  • Expert in Python and SQL.
  • Experience with modern software development best practices, e.g., agile software development, code reviews, unit testing, version control (e.g., git), CI/CD.
  • Experience with microservice architectures.
  • Experience working in an agile team.
  • Experience with ML frameworks and tools (e.g., pandas, numpy, scikit-learn, TensorFlow, Pytorch, Spark MLlib).
  • Experience with cloud-based services, such as Azure, AWS, etc.
  • Experience with modern ETL, compute, and orchestration frameworks, e.g., Apache Spark, Apache Flink, Apache Kafka, etc.
  • Experience with container technologies, e.g., Docker, Kubernetes.
  • Experience in building machine learning or AI systems.
  • Experience deploying models to production.
  • Experience working with ML platforms, e.g., MLflow, Kubeflow, etc.
  • Experience with cloud-based infrastructure, e.g., Azure, AWS, GCP; ideally AWS.
  • Experience with robotic automation of processes within the Financial Services industry.
Attributes:
  • Self-motivated and assertive.
  • Strong analytical ability.
  • Strong verbal and written communication/presentation skills.
  • Team player and ability to operate independently.
  • Good interpersonal skills.
  • Trustworthy.
  • Ability to prioritize.
  • Ability to work in a pressured environment.
  • Deadline-driven.