· Data Pipeline Management o Maintain and optimize training data pipelines leveraging the latest big data tools with an emphasis on cost-effectiveness and reliability
· Model Lifecycle Management o Onboard new ML models onto the existing platform with standardized training automation and interfaces
· MLOps o Maintain and enhance CI/CD pipelines for ML data & model pipelines o Operate sign-off and deployment processes, ensuring high quality model sign-off
· Quality Dashboards o Design and develop quality dashboards to monitor the quality and reliability of both models as well as data artifacts produced
Key Qualifications
· Bachelor's degree in Computer Science, Engineering, or a related field.
· Minimum 5 years of experience in software engineering with a focus on full-stack development and infrastructure.
· Prior hands on experience in ML model productionalization and operationalization
· Familiarity with ML frameworks such as Sklearn, PyTorch, Tensorflow
· Familiarity with data processing frameworks such as Spark
· Familiarity with contemporary CI/CD and MLOps best practices.
· Strong problem-solving and analytical skills.
· Proven track record of working independently and as part of a distributed global team.