Data Engineer - Machine Learning

Job Description

As an MLOps Engineer, you will be responsible for the design, development, integration and deployment of frameworks, tools and pipelines required for the end-to-end machine learning lifecycle in projects.

You will apply MLOps technologies to operationalize AI solutions at scale, integrated with client’s business processes and applications. You will be responsible for providing technical contribution and/or leadership in the creation and delivery of MLOps solutions designed to meet business needs and drive outcomes.

About you:

• Knowledge of data platforms and experience with data processing tools.
• Familiarity with machine learning platforms, frameworks, and tools.
• Experience with MLOps platforms and tools
• Understanding of AI infrastructure and deployment.

Qualifications:

• Bachelor’s/Master’s degree in Computer Science, Engineering, or a related field.
• Total of 3-6 years of experience in managing machine learning projects end-to-end, with the last 18 months focused on MLOps. Knowledge of machine learning frameworks: Proven experience in MLOps, DevOps, or a related field.
• Strong problem-solving and troubleshooting skills.
• Excellent communication and collaboration skills.
• Knowledge of security practices in machine learning systems.
• Previous experience in a similar role within the ML/AI domain.

Responsibilities:
Infrastructure and Environment Management:

• Design, implement, and manage scalable and reliable infrastructure for machine learning models and applications.
• Ensure seamless integration of machine learning models into production systems.

Continuous Integration/Continuous Deployment (CI/CD):

• Develop and maintain CI/CD pipelines for automating the deployment of machine learning models.
• Implement version control and release management practices for machine learning assets.

Model Deployment and Monitoring:

• Deploy machine learning models to production environments and monitor their performance.
• Implement monitoring solutions to detect and address issues related to model drift, data quality, and system health.

Collaboration with Data Scientists and Engineers:

• Collaborate with data scientists to understand model requirements and facilitate the transition of models from research to production.
• Work closely with engineers to integrate machine learning solutions into existing applications.

Security and Compliance:

• Implement security best practices for machine learning systems.
• Ensure compliance with relevant regulations and industry standards.

Automation and Scripting:

• Develop automation scripts and tools to streamline the MLOps processes.
• Implement best practices for code and configuration management.

Troubleshooting and Incident Response:

• Provide support for troubleshooting issues related to machine learning models in production.
• Develop and implement incident response plans for machine learning systems.

Documentation:

• Maintain comprehensive documentation for MLOps processes, workflows, and configurations

Job Details

Take note that applications will not be accepted on the below date and onwards, kindly submit applications ahead of the closing date indicated below.

07/12/24

All appointments will be made in line with FirstRand Group’s Employment Equity plan. The Bank supports the recruitment and advancement of individuals with disabilities. In order for us to fulfill this purpose, candidates can disclose their disability information on a voluntary basis. The Bank will keep this information confidential unless we are required by law to disclose this information to other parties.