Principal Machine Learning Engineer

We are looking for a Principal Machine Learning Engineer to help us build the next generation of Sage's AI and machine learning capabilities. In this role, you will work closely with our product and engineering teams to develop and deploy machine learning models that power our products and services, helping drive innovation and deliver value to our customers. You will be responsible for the full life cycle of model development, from data collection and preprocessing to model training, deployment, and monitoring. Key Responsibilities: - Design and develop high-performance, scalable machine learning models to solve complex business problems - Collaborate with cross-functional teams to define and prioritize machine learning initiatives - Implement best practices for model operationalization, including CI/CD pipelines, monitoring, and incident response - Stay up-to-date with the latest advancements in machine learning and AI and identify opportunities to apply new techniques - Mentor and guide more junior team members, sharing your expertise and helping to build a strong machine learning practice Requirements: - Significant experience building and deploying machine learning models in production environments - Strong background in Python, including libraries like NumPy, Pandas, Scikit-learn, and TensorFlow/PyTorch - Proficiency in data engineering, with experience working with large-scale data pipelines and data stores - Excellent problem-solving and critical thinking skills, with the ability to tackle complex challenges - Strong communication skills and the ability to translate technical concepts to non-technical stakeholders - Familiarity with cloud-based machine learning platforms (e.g., AWS SageMaker, Google AI Platform, Azure ML) is a plus

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