Staff Software Engineer - (Matching and Recommendations)

About the role

At Bumble, we're building a world where all relationships are healthy and equitable, and machine learning is central to making that a reality for millions of people every day. As part of our Machine Learning team in Recommendations, you'll help shape intelligent systems that power meaningful connections, safer interactions, and more personalized experiences across our platform.

Responsibilities

• Own the technical direction for Bumble’s recommendations platform, evolving the systems that serve recommendations for millions of members.
• Identify the highest‑leverage engineering investments across retrieval, ranking, and serving, while balancing relevance, marketplace health, reliability, and latency.
• Lead the design of large‑scale distributed systems that power recommendations across multiple teams and domains, covering online serving, feature delivery, experimentation, and feedback loops; keep them simple, resilient, scalable, and elegant.
• Identify and solve the highest‑leverage technical problems across the recommendations stack, clarify ambiguous architectural decisions, and create solutions that help multiple teams move faster.
• Raise the bar for engineering quality through technical leadership—establish architectural principles, engineering standards, observability practices, and operational excellence.
• Multiply the impact of other engineers by mentoring senior engineers, influencing technical direction across teams, and sharing context and judgment on the organization’s most challenging problems.
• Drive platform evolution for the long term by leading foundational initiatives such as service decomposition, recommendation infrastructure, experimentation capabilities, developer tooling, and AI‑assisted engineering.
• Remain deeply technical through hands‑on contribution: write and review high‑quality code, contribute to critical designs, prototypes, and production code, rapidly prototype new ideas, and serve as a trusted expert for the most critical parts of the recommendations platform.

Requirements

• Typically requires 8+ years of building large‑scale backend or distributed systems, with experience delivering complex technical initiatives that span multiple teams.
• Deep expertise in designing and operating high‑scale distributed systems, strong experience in modern languages such as Go, Kotlin, Java, or similar, and a track record of building reliable production platforms.
• 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, collaboration, and sound technical judgment.
• Proven experience partnering closely 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 by improving systems, tooling, architecture, and the effectiveness of the wider engineering organization.
• Strong AI fluency—using modern AI‑assisted engineering tools to improve productivity while applying thoughtful human judgment, maintaining high engineering standards, and ensuring member trust remains central to every technical decision.

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), mapping APIs, GPS services, or other 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.

About Us

Bumble Inc. is the parent company of Bumble Date, BFF, and Badoo. The Bumble platform enables people to build healthy and equitable relationships, through Kind Connections. Founded by Whitney Wolfe Herd in 2014, Bumble was one of the first dating apps built with women at the center and connects people across dating (Bumble Date) and friendship (BFF). BFF is a friendship app where people in all stages of life can meet others nearby and create meaningful platonic connections and community based on shared interests. Badoo, founded in 2006, is one of the pioneers of web and mobile dating products.