Machine Learning Engineer, Nory

• This role is ideal for a senior independent doer, someone who has owned the entire ML lifecycle and is ready to ship meaningful, production-grade ML systems from scratch
• Background: Master's Degree in a STEM subject, with a significant statistics component
• Full Lifecycle Ownership: At least 3 years of experience taking ML systems from idea through to production in a commercial setting - repeatedly and successfully. You’re confident in owning the process independently, from problem formulation to monitoring impact in production
• Technical Proficiency: Strong Python and experience with ML libraries (e.g., Scikitlearn, Pandas, LightGBM), plus working knowledge of cloud infrastructure and data tools (Snowflake, DBT, Omni)
• Structured Thinking: You use a clear and repeatable process to approach ML problems, including problem formulation, KPI definition, and experimental design
• Rigour & Impact: You apply rigorous statistical and experimental thinking, and can demonstrate how your work has driven measurable business outcomes
• Collaboration: You thrive in highly collaborative environments, communicate clearly, and offer help where needed to improve team outcomes
• Startup mindset: You thrive in fast-paced environments, move quickly, and take initiative to maintain momentum and resolve issues efficiently. You are comfortable with ambiguity and multitask effectively while delivering real impact

Desirable

• We’re now looking for a Machine Learning Engineer to join our Data team
• This is not a research or experimentation role; it's about building systems that work in the real world and move the needle on customer outcomes and business impact
• Own the end-to-end development of machine learning systems, from business problem formulation and algorithm design through to deployment and monitoring in production
• Collaborate with product managers and engineers to define KPIs, design data flows, and embed algorithms in product features
• Apply best-in-class ML practices with clear problem framing, model evaluation, experimentation, and observability- to deliver real-world impact
• Independently lead the development of models across the platform acting as the primary ML owner and act as the primary ML owner; from data access and cleaning to modelling and integration
• Work autonomously while contributing to a culture of collaboration, shared learning, and continuous improvement
• Actively participate in peer reviews, team rituals, and cross-functional discovery, sharing insight and offering help where needed