Smart Working Solutions - Machine Learning Engineer (Remote, Full-Time) [AS207]

• Architect, implement, and maintain production-grade, low-latency ML services for ranking, recommendation, and forecasting use cases • Collaborate with data scientists, product managers, and engineers to identify the best technical approaches to product and infrastructure challenges • Design and support experimentation frameworks to test hypotheses and measure improvements to models • Advise on data strategy, ensuring high-quality, well-structured datasets are available for current and future data science initiatives • Deliver machine learning models that meet agreed engineering standards, ensuring scalability, resilience, and long-term maintainability • Enhance and evolve an AWS-native MLOps platform, supporting high availability and low-latency inference • Monitor, maintain, and continuously improve deployed models in production environments • Contribute positively to team culture, demonstrating curiosity, ownership, and a bias toward learning and improvement • 5+ years of total professional experience, operating at a senior engineering level • 3+ years of hands-on experience in Machine Learning, including taking models from experimentation to production • 3+ years of experience with Python, writing production-quality, maintainable code • 3+ years of experience working with SQL in analytical or data-intensive environments • Strong experience building and operating production ML systems, including model serving and monitoring • Solid understanding of experimentation, model evaluation, and performance trade-offs in real-world systems • Experience working closely with cross-functional teams in a collaborative, product-focused environment • Strong engineering mindset, with a focus on scalability, reliability, and future-proof solutions • 1+ year of experience with Snowflake, or strong experience with modern cloud data warehouses • 1+ year of experience with dbt, or hands-on experience building and maintaining analytical data models • Experience contributing to or improving MLOps platforms, including CI/CD for ML, monitoring, and inference optimisation • Familiarity with AWS-native data or ML tooling • Experience working in high-scale, consumer-facing or e-commerce environments • A proactive, curious mindset aligned with values such as continuous learning, thoughtful problem-solving, and positive collaboration