Senior Machine Learning Platform Engineer

Join Hinge, a dating app on a mission to create meaningful connections. As a Senior Machine Learning Platform Engineer, you'll play a crucial role in democratizing AI for Hinge, ensuring it remains accessible, robust, scalable, cost-efficient, and trusted. You'll collaborate with various teams and external stakeholders, optimize the AI/ML development and deployment process, and help define the future of machine learning within the company. Enjoy a range of benefits, including hybrid work options, health insurance, paid time off, parental leave, wellness programs, professional growth opportunities, and more.

• Collaborate with product and platform teams to optimize machine learning solutions and deliver value incrementally.
• Own or contribute to technical designs for various platforms, including feature, training, serving, and AI observability platforms.
• Develop, maintain, and enhance frameworks for AI/ML model development and deployment while establishing best practices in MLOps.
• 1+ year of experience leading projects with at least 1 other team member through completion
• 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 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
• ML knowledge: A basic understanding of ML algorithms, techniques, and best practices
• Cloud platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure
• Strong written communication: The ability to communicate complex ideas and technical knowledge through documentation
• Software leadership skills: A track record of leading projects through completion with quantifiable and measurable outcomes
• 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.
• System design & architecture: Ability to design scalable and efficient ML systems
• Data engineering knowledge: Skills in handling and managing large datasets including, data cleaning, preprocessing, and storage
• 4+ years of experience, depending on education, as an ML, backend, data, or platform engineer developing and working with large scale, complex systems