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Bumble is seeking a Staff Software Engineer to own the technical direction of its recommendations platform, which powers intelligent systems connecting millions of members across dating and friendship products. This is a foundational role on a small, dynamic machine learning team where you'll shape the next generation of AI-driven online connection experiences.
You will own the technical strategy for the recommendations platform, identifying the highest-leverage engineering investments across retrieval, ranking, and serving while balancing relevance, marketplace health, reliability, and latency. You'll lead the design of large-scale distributed systems that power recommendations across multiple teams and domains, from online serving and feature delivery to experimentation and feedback loops. Your responsibilities include solving the highest-leverage technical problems across the recommendations stack, bringing clarity to ambiguous architectural decisions, and creating solutions that help multiple teams move faster.
As a technical leader, you'll raise the bar for engineering quality by establishing architectural principles, engineering standards, observability practices, and operational excellence. You'll multiply the impact of other engineers by mentoring senior engineers, influencing technical direction across teams, and sharing context on the organization's most challenging problems. You'll drive platform evolution through foundational initiatives such as service decomposition, recommendation infrastructure, experimentation capabilities, developer tooling, and AI-assisted engineering.
Despite the staff-level scope, you remain deeply technical—writing and reviewing high-quality code where it creates the greatest leverage, contributing to critical designs and production code, and rapidly prototyping new ideas. You'll serve as a trusted expert for the most critical parts of Bumble's recommendations platform.
Bumble Inc. is the parent company of Bumble Date, BFF, and Badoo, connecting people across dating and friendship. Founded in 2014 by Whitney Wolfe Herd, Bumble was one of the first dating apps built with women at the center.
Requirements:
- 8+ years of experience building large-scale backend or distributed systems, with a track record of delivering complex technical initiatives spanning multiple teams
- Deep expertise in designing and operating high-scale distributed systems with strong experience in modern languages such as Go, Kotlin, Java, or similar
- Strong understanding of recommendation systems, ranking architectures, or other large-scale decision systems, including retrieval, candidate generation, ranking, feature serving, experimentation, and feedback loops
- Experience building cloud-native systems on Google Cloud Platform (GCP) or comparable public cloud infrastructure, with deep knowledge of scalability, resilience, observability, and operational excellence
- Demonstrated ability to define technical strategy and influence architectural direction across multiple engineering teams through expertise and collaboration rather than organizational authority
- Proven experience partnering with Product, Data Science, Machine Learning, and Engineering leadership to translate ambiguous business problems into durable technical solutions
- Track record of mentoring senior engineers, raising engineering standards, and creating leverage through improved systems, tooling, and architecture
- Strong AI fluency, using modern AI-assisted engineering tools while maintaining high engineering standards and ensuring member trust
Nice to Have:
- Experience building recommendation systems, search platforms, personalization engines, or other intelligent decision systems
- Experience with geospatial technologies, GIS platforms, routing systems, spatial databases (e.g., PostGIS), or location-aware applications
- Experience building platforms or shared infrastructure used by multiple engineering teams
- Familiarity with experimentation platforms, feature delivery systems, event-driven architectures, or real-time data processing
- Experience building consumer-facing products at scale
