Machine Learning Engineer

Solid foundation in traditional ML techniques and the model lifecycle. Practical expertise to handle class imbalance, tune hyperparameters, and resolve common pitfalls like overfitting. Demonstrable experience designing, deploying, and monitoring ML services to solve customer and business problems. Strong programming skills in Python for delivering production-ready, well-structured and documented code. Experience with large datasets and proficiency with SQL. Exposure to Snowflake and dbt is a plus. Curious about customer needs and takes a pragmatic, data-driven, and experimental approach to solving problems. Thrive in collaborative environments and work effectively with a range of people and teams. Bring a positive, optimistic mindset, overcoming setbacks and motivating those around you. Keen to learn and stay up-to-date with the latest technologies and value sharing knowledge with peers. Experience working on an e-commerce site or in a fast-growing start-up. Experience working in a fully-remote setting.

Architecting, implementing, and maintaining production-grade, low-latency ML services for ranking models, recommendation algorithms, and forecasting methods. Collaborate with data scientists, product managers and other teams to brainstorm best approaches for solving problems. Help design experimentations to test ideas and assess improvements to models. Advise on data strategy to provide datasets for future data science projects. Deliver ML models with agreed engineering standards to ensure resilience, scalability and future-proofing. Enhance AWS-native MLOps platform, and guarantee high availability and low-latency inference for models. Bring energy and positivity, looking for opportunities to learn and craft the role around values.