Chief Machine Learning Innovation Officer

2 weeks ago

Cork, Cork, Ireland beBeeTransformation Full time
Transform Enterprise AI Initiatives

This is a dynamic opportunity for a Senior Machine Learning Operations Engineer to lead the charge in transforming enterprise AI initiatives. The successful candidate will be at the forefront of our big bet AI projects, harnessing the power of machine learning to drive innovation across the organization.

The role involves taking the helm in the full project lifecycle, focusing on deploying and managing solutions within our MLOps enterprise platform. This includes engaging in a wide array of ML engineering activities, from Ops and Modeling to Data Engineering, ensuring a comprehensive approach to enterprise solutions.

Key Responsibilities:
  • End-to-End ML Engineering: Engage in a wide array of ML engineering activities, from Ops and Modeling to Data Engineering, ensuring a comprehensive approach to enterprise solutions.
  • Innovative Model Design: Collaborate with business leadership and Data Science teams to design, build, and deliver ML models that tackle real-world business challenges.
  • Strategic Infrastructure Decisions: Utilize your deep understanding of ML techniques to inform infrastructure choices, considering model types, data selection, hyperparameter tuning, and validation.
  • Complex Problem Solving: Write and test application code, develop and validate ML models, and automate testing and deployment processes to tackle complex problems.
  • Model Management: Retrain, maintain, and monitor models in production, ensuring they perform optimally and adapt to changing data landscapes.
  • Cloud-Based Optimization: Leverage cloud-based architectures to deliver scalable and efficient ML models.
  • Data Pipeline Construction: Develop optimized data pipelines to support ML models with high-quality data in collaboration with data engineering.
  • CI/CD Excellence: Implement continuous integration and deployment best practices, including test automation and monitoring, to ensure successful model deployments.
  • Governance and Best Practices: Manage code to minimize vulnerabilities, govern models from a risk perspective, and adhere to Responsible and Explainable AI principles.


Requirements:
  • 7+ years industry experience.
  • 4+ years programming experience with Python.
  • 3+ years designing and building data-intensive solutions with distributed computing.
  • 2+ years with industry-recognized ML frameworks (scikit-learn, PyTorch, TensorFlow, Spark, Ray).
  • 1+ year productionizing, monitoring, and maintaining models.


Preferred Qualifications:
  • 1+ years building, scaling, and optimizing ML systems.
  • 1+ years in data gathering and preparation for ML models.
  • 2+ years developing performant, resilient, and maintainable code.
  • Experience with Azure for developing, deploying, and monitoring of production ML solutions.
  • Advanced degree in computer science, electrical engineering, mathematics, or a related field.

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