Senior Machine Learning Engineer

About the role

Responsibilities

• Develop, improve, and maintain machine learning models that capture demand and supply dynamics within a digital manufacturing marketplace.
• Build and refine pricing-related models supporting intelligent and automated quoting.
• Develop models for cost estimation from CAD geometry, demand forecasting, and partner routing probability.
• Apply a range of machine learning techniques, including tree-based methods, probabilistic models, and deep learning, to solve both new and existing business challenges.
• Translate complex marketplace inputs such as part geometry, order history, and partner capacity into meaningful model features.
• Design, build, and maintain reliable machine learning training and inference pipelines on AWS.
• Develop scalable workflows for experimentation, model training, validation, and deployment.
• Apply appropriate model versioning and experiment tracking practices.
• Build solutions that support reliable production machine learning systems.
• Contribute to scaling ML infrastructure as model and business requirements evolve.
• Conduct offline experiments to evaluate and validate model improvements before deployment.
• Apply A/B testing and backtesting approaches to assess model performance.
• Monitor models in production and proactively identify model drift, degradation, or unexpected behaviour.
• Support monitoring, alerting, and retraining workflows to maintain model performance over time.
• Continuously improve models based on production performance and evolving business requirements.
• Work closely with ML Engineers, Data Scientists, Product teams, and domain experts in cross-functional teams.
• Collaborate with stakeholders to understand marketplace dynamics and translate business challenges into machine learning solutions.
• Work with real-world, complex, and imperfect datasets to develop practical solutions to ambiguous problems.
• Communicate model behaviour, results, and technical considerations effectively across technical and non-technical stakeholders.
• Contribute to the development of machine learning capabilities that support manufacturing intelligence and business growth.
• Mentor and support mid-level and junior engineers within the team.
• Share machine learning engineering practices, technical knowledge, and lessons learned.
• Contribute to a collaborative engineering environment focused on continuous learning and improvement.
• Stay up to date with advancements in machine learning, particularly in pricing, marketplace modelling, and manufacturing intelligence.
• Evaluate emerging approaches and techniques that could improve model performance and business outcomes.
• Apply relevant advances pragmatically to production machine learning challenges.