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In today’s digital world, finding genuine relationships is tougher than ever. At Hinge, we’re on a mission to inspire intimate connection to create a less lonely world. We’re obsessed with understanding our users’ behaviors to help them find love, and our success is defined by one simple metric– setting up great dates. With tens of millions of users across the globe, we’ve become the most trusted way to find a relationship, for all.

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Hing

ABOUT THE ROLE

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!

RESPONSIBILITIES

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• Define the long-term, holistic roadmap for the Feature Store platform, aligning it with company-wide ML initiatives and ensuring end-to-end integration with model training, serving and observability platforms.

• Evaluate and introduce new technologies, tools and best practices that enhance feature serving reliability, scalability, cost efficiency and throughput, including leading build vs buy discussions.
• Architect, build, and maintain frameworks enabling MLEs for self service data ingestion and serving pipelines for both offline (batch, async) and online (low-latency) feature stores.
• Partner with cross-functional Platform teams to represent feature engineering requirements and incorporate them into Hinge’s wider Platform capabilities.
• Collaborate closely with ML Engineers, Data Scientists, and Product Managers to understand the ML development lifecycle and identify opportunities to accelerate the AI/ML development and deployment process.
• Mentor and educate ML Engineers and Data Scientists on current and up and coming methods, tools and technologies for Feature Engineering.
• Help design and architect an AI platform that adheres to the principles of responsible AI and simplifies privacy compliance.