
Machine Learning Data Engineer
4 days ago
Overview
Machine Learning Data Engineer
at IntelligenceBank will apply data-driven decisions and high code quality to enhance and maintain core ML systems, including data processing pipelines, a rule engine, and a content extractor. We are looking for an experienced engineer with expertise in Python, ML/AI system development, and MLOps.
IntelligenceBank is a digital asset management and marketing operations platform for brands in regulated markets, helping brands go to market quickly, stay on brand, and ensure regulatory compliance. Our headquarters are in Melbourne, Australia, with offices across the US, Canada and the UK.
Responsibilities
Maintain existing functionality and assist in design and development of new features for key ML/AI system components:
Content Extractor
Rule Engine
Data processing pipelines
Ensure resilient and highly available ML/AI systems including production and development environments, deployments, and general operations for ML/AI within the Marketing Compliance areas of IntelligenceBank
Assist in the design and documentation of system architectures for existing and future projects
Participate in Agile ceremonies such as Stand-up, Retrospectives and Planning Sessions for the ML/AI roadmap
Qualifications
Expert level Python and software design skills
Advocate for test automation and code health
Experience with AWS and GCP platforms
Experience with MLOps processes and tooling and a passion for increasing MLOps maturity
Experience in Computer Vision (e.g., YOLO)
Experience in Natural Language Processing
Generative AI experience including prompt engineering for NLP and CV tasks and running comparative evaluations
Additional Information
Next Steps: After applying, your application will be reviewed by our team and you'll be updated by phone or email regarding status. Our process includes phone screening, interviews addressing our values and role requirements, and references and criminal history checks. We are a Circle Back Employer and commit to replying to every applicant.
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