Machine Learning Operations Engineer Flash 2023-04-12 Cape Town CBDJob Ref #: FH-198Industry: FintechJob Type: PermanentPositions Available: 1
We are looking for a Machine Learning Engineer to lead the designing and executing of the ML Ops strategy for the Data Science team. For this role, you should have significant experience in working with a variety of technologies related to Data Ops, ML Ops and AI. Critical thinking and problem-solving skills are essential for overcoming challenges to build and support a top-class platform.
Job Description Responsibilities:
Contribute to the Data Science and AI strategy, particularly the strategy for operationalizing machine learning models
Design and build automated, scalable and reliable Machine Learning CI/CD pipelines, including automatic re-training, re-testing and re-deploying
Manage and monitor productionized machine learning models
Enhance data collection procedures to include information that is relevant for building analytic systems
Assist in the integration and development of an external analytics system, which involves various data processing and data science technologies
Enable smarter processes and implement analytics for meaningful insights
Keep current with technical and industry developments
Communicate findings to all stakeholders
Job Requirements Minimum Requirements:
B. Sc or B. Com in Physics, Computer Science, Applied Mathematics, Statistics, Data Science, Software Engineering or similar
5+ years of relevant professional experience, preferably in the fintech industry
Knowledge / Skills:
Strong analytical and problem-solving skills
Expert in Python and SQL
Experience with the 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 prioritise
Ability to work in a pressured environment
Deadline driven #LI-AR1
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