Hinge is hiring an experienced Staff ML Platform Engineer to drive the design, development and evolution of our Feature Store platform. You will own our streaming offline and online feature store capabilities, enabling Machine Learning Engineers (MLEs) to efficiently perform data exploration and feature engineering operations and utilize features for model training and model inference (batch, near real-time and online). You will collaborate closely with ML engineers, data scientists, data engineers, partner platform teams and project managers to ensure that our Feature Store scales to meet the growing data demands of our ML teams, provides intuitive workflows for feature management and satisfies requirements for data privacy and legal frameworks at Hinge.

This role requires awareness and empathy for the applied AI/ML problem space. You will ensure that the Feature Store platform is truly self-service and serves the evolving needs of all ML stakeholders without incurring a linear operations burden. You will also be deeply integrated with the rest of the AI platform and understand data access patterns across the entire ML lifecycle. Your success will depend on maintaining a cohesive, end-to-end view of how data is used in early model experimentation, training, evaluation and inference in production. Being part of a small yet highly impactful team means having a broad scope of responsibility, and as ML is still in its early stages at Hinge, this role provides a chance to grow as a technical leader by mentoring others on the team and across the company. This is an exciting opportunity to own and help define the future of machine learning within a rapidly growing team!