Senior ML Platform Engineer

Hinge is the dating app designed to be deleted

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.

Joining Hinge’s AI Platform Core team offers a unique opportunity to help define and contribute to a budding ML platform with the goal of accelerating the development, deployment, and operations of AI enabled features on Hinge. If you are excited by the idea of working on challenges ranging from establishing our initial training and serving frameworks, building millisecond real-time predictions at scale, automating the machine learning model lifecycle, implementing model monitoring, and building support for generative AI models, then read on!

With a mission to democratize AI for Hinge, ensuring it remains easily accessible, robust, scalable, cost-efficient, and trusted you'll collaborate across our product and engineering teams, as well as with external stakeholders. You will meet our internal customers where they are and optimize towards their needs by delivering value incrementally and coupled to their problems. Being part of a small yet 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 leader by mentoring others across the company.

This is an exciting opportunity to own and help define the future of machine learning within a rapidly growing team!

• Own or contribute to technical designs for the feature platform, training platform, serving platform, and underlying operational infrastructure that provides incremental delivery and impact.
• Develop, maintain, and enhance reusable frameworks for AI/ML model development and deployment while establishing and driving best practices in machine learning engineering and MLOps.
• Design, advocate, and implement for availability, scalability, operational excellence, and cost management while delivering incrementally.
• Collaborate closely with ML Engineers, Data Scientists, and Product Managers to understand their needs 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 tools and technologies for ML operations through presentations and documentation.
• Help design and architect an AI platform that adheres to the principles of responsible AI and simplifies privacy compliance.
• Lead build vs buy discussions on technologies that would underpin the feature, training, and serving layers.

• 3+ years of experience, depending on education, as an ML, backend, data, or platform engineer developing and working with large scale, complex systems.
• 2+ years of experience working on a cloud environment such as GCP, AWS, Azure, and with dev‑ops tooling such as Kubernetes
• 1+ year of experience leading projects with at least 1 other team member through completion.
• 1+ year of experience for Senior designing and developing online and production grade ML systems.
• A degree in computer science, engineering, or a related field.
• Strong programming skills: Proficiency in languages like Python, Go, or Java.
• System design & architecture: Ability to design scalable and efficient ML systems.
• Cloud platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure.
• ML knowledge: A basic understanding of ML algorithms, techniques, and best practices.
• Data engineering knowledge: Skills in handling and managing large datasets including, data cleaning, preprocessing, and storage
• Collaboration and communication skills: The ability to work effectively in a team and communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds.
• Strong written communication: The ability to communicate complex ideas and technical…